21ODMPT655-Research Methods and Statistics –I

Research Design 45 2. Conclusive Research Design Conclusive Research Design is typically more formal and structured than exploratory research. It is based on large representative samples and the market information obtained is subjected to quantitative analysis. It is designed to assist the decision-maker in determining, evaluating and selecting the best course of action to take in a given situation. It involves providing information on evaluation of alternative courses of action and selecting one from among a number available to the researcher. It is again classified as: (i) Descriptive research and (ii) Causal research. (i) Descriptive Research Descriptive research is undertaken when the researcher desires to know the characteristics of certain groups such as age, gender, occupation, income or education. The objective of descriptive research is to answer the “who, what, when, where and how” of the subject under study/investigation. Descriptive studies are again classified into two types: (a) Longitudinal Research relies on panel data and panel methods. It involves fixing a panel consisting of fixed sample of subjects that are measured repeatedly. The panel members are those who have agreed to provide information at specific intervals over an extended period. For example, data obtained from panels formed to provide information on market shares are based on an extended period of time but also allow the researcher to examine changes in market share over time. New members may be included in the panel as and when there is a dropout of the existing members or to maintain representativeness. (b) Cross-sectional Research is the most predominantly and frequently used descriptive research design in marketing. It involves a sample of elements from the population of interest. The sample elements are measured on a number of characteristics. Cross-sectional study is a study involving a sample of elements from the population of interest at a single point of time. It is a study concerned with a sample of elements from a given population. CU IDOL SELF LEARNING MATERIAL (SLM)

46 Research Methods and Statistics - I Uses of Descriptive Research Descriptive research is conducted for the following reasons: (a) To describe the characteristics of relevant groups, such as consumers, salespeople, or organisations or market areas. (b) To estimate the percentage of units in a specified population exhibiting a certain behaviour, e.g., the percentage of heavy users of prestigious department stores who also patronise discount department stores. (c) To determine the “perceptions of product characteristics, e.g., how do households perceive the various department stores in terms of salient factors of the choice criteria? (d) To determine the degree to which marketing variables are associated, e.g., to what extent is shopping at department stores related to eating out? (e) To collect demographic information of consumers/users of a product under study. (f) To discover the relationship between certain variables, e.g., sale of toothpaste among rural population and urban population or rate of savings among low, middle and higher income groups. (ii) Causal Research Casual research design is the third type of research design. As the name indicates, casual design investigates the cause and effect relationship between two or more variables. This design measures the extent of relationship between the variables. Casual research designs attempt to specify the nature of functional relationship between two or more variables. It is used to obtain evidence of cause-and-effect relationships which is otherwise known as the independent-dependent relationship or the predictive relationship. Causal research requires a strong degree of planning on the design as its success depends on the structure of the design. This is an important type of research useful for marketers as this allows marketers to base their decisions on assumed causal relationships. CU IDOL SELF LEARNING MATERIAL (SLM)

Research Design 47 Causal research is done in the following situations: (a) To identify which variables are the cause and which are the effect. In statistical terms, causal variables are called independent variables and effectual variables are called dependent variables. (b) To determine the nature of the relationship between the causal variables and the effect to be predicted. The casual research design is based on reasoning. The designs for casual research can be divided into three categories: (a) Historical, (b) Survey and (c) Experimental. 3. Experimental Research Design Experimental research studies generally require testing of hypothesis for causal relationship amongst the variables. Naturally, these types of research studies require procedures that should not only reduce the bias but also lead to inferences about causality. This leads to necessity for experimental designs. Experimental design develops a framework of experiments based on thumb rule or statistical procedures. 3.10 Summary Research design provides the glue that holds the research project together. A design is used to structure the research, to show how all of the major parts of the research project, the samples or groups, measures, treatments or programmes, and methods of assignment, work together to try to address the central research questions. A research design is the arrangement of conditions for collections and analysis of data in a manner that aims at relevance to the research purpose with economy in procedure. In fact, research design is the conceptual structure within which research is conducted; it constitutes the blueprint for collection, measurement and analysis of data. A research design encompasses the methodology and procedures employed to conduct scientific research. The design of a study defines the study type (descriptive, correlation, semi-experimental, experimental, review and meta-analytic) and sub-type (e.g., descriptive-longitudinal case study), research question, hypotheses, independent and dependent variables, experimental design, and, if applicable, data collection methods and a statistical analysis plan. CU IDOL SELF LEARNING MATERIAL (SLM)

48 Research Methods and Statistics - I The research design is a plan of action indicating the specific steps that are necessary to provide answers to those questions, test the hypotheses, and thereby achieve the research purpose that helps choose among the decision alternatives to solve the management problem or capitalise on the market opportunity. 3.11 Key Words/Abbreviations  Research Design: Research design provides the glue that holds the research project together.  Exploratory Research Design: Exploratory research is conducted when the researcher does not know how and why certain phenomenon occurs.  Conclusive Research Design: Conclusive Research Design is typically more formal and structured than exploratory research.  Longitudinal: Longitudinal Research relies on panel data and panel methods.  Cross-sectional: Cross-sectional Research is the most predominantly and frequently used descriptive research design in marketing.  Causal Research: Casual research design is the third type of research design. 3.12 Learning Activity 1. You are suggested to prepare a report on “Research Design” and its managerial implications. _________________________________________________________________ _________________________________________________________________ 2. You are required to prepare live project on social issues and identify the research gap using exploratory research design. _________________________________________________________________ _________________________________________________________________ 3. You are requested to identify the difference between exploratory research design and conclusive research design. _________________________________________________________________ _________________________________________________________________ CU IDOL SELF LEARNING MATERIAL (SLM)

Research Design 49 3.13 Unit End Exercises (MCQs and Descriptive) Descriptive Type Questions 1. What is Research Design? Explain the features of Research Design. 2. Discuss the characteristics of a Good Research Design. 3. Explain the nature of Research Design. 4. Discuss the concept of Research Design. 5. Explain the process of Research Design Preparation. 6. Discuss the various types of Research Design. Multiple Choice Questions 1. Which of the following design is used to structure the research, to show how all of the major parts of the research project, the samples or groups, measures, treatments or programmes? (a) Research Design (b) Data Collection (c) Data Analysis (d) All the above 2. Which of the following can be achieved by a longitudinal research design? (a) Mapping of change in an organisation (b) The change in employment relations over a number of years (c) The experiences of employees, who begin work on the same day (d) All of the above 3. Which of the following types of cases is the most common within business and management research? (a) Single organisation (b) A person (c) Single event (d) Single location CU IDOL SELF LEARNING MATERIAL (SLM)

50 Research Methods and Statistics - I 4. In which of these studies is validity in question? (a) Qualitative (b) Positivist (c) Quantitative (d) None of the above 5. The collection of data using questionnaires, but it also includes other techniques which is strategy? (a) Action research (b) Ethnography (c) Grounded theory (d) Survey 6. The researcher is involved in the acts under studies/he causes changes and monitors the outcomes which research strategy? (a) Survey (b) Action research (c) Case study (d) Grounded theory 7. What is an activity and time passed plan? (a) Research design (b) Research (c) Design (d) Validity 8. What is a guide for selecting sources and types of information? (a) Research design (b) Research (c) Both (d) None Answers: 1. (a), 2. (d), 3. (d), 4. (a), 5. (d) 6. (b), 7. (a), 8. (a) 3.14 References References of this unit have been given at the end of the book.  CU IDOL SELF LEARNING MATERIAL (SLM)

Experimental Design 51 UNIT 4 EXPERIMENTALDESIGN Structure: 4.0 Learning Objectives 4.1 Introduction 4.2 Concept of Experimental Design 4.3 Concept of Independent Variables 4.4 Concept of Dependent Variables 4.5 Experimental Research Design 4.6 Need for Experimental Research Design 4.7 Basic Principles of Experimental Research Design 4.8 Types of Experimental Designs 4.9 Advantages of Experimental Research 4.10 Disadvantages of Experimental Research 4.11 Summary 4.12 Key Words/Abbreviations 4.13 LearningActivity 4.14 Unit End Exercises (MCQs and Descriptive) 4.15 References CU IDOL SELF LEARNING MATERIAL (SLM)

52 Research Methods and Statistics - I 4.0 Learning Objectives After studying this unit, you will be able to:  Explain the various types of designs  Describe need for experimental research design  Explain the various types of experimental designs 4.1 Introduction Experimental research designs are also widely used in psychology, education and the social sciences, and are considered the gold standard for evaluating causal hypotheses. Their logic as illustrated above is straightforward, though their actual execution can be quite challenging. First, all experimental research designs are based on comparison between two or more groups. These groups must be composed of subjects who are similar on all characteristics which might influence the outcome of interest; otherwise, it is impossible to rule out the possibility that any observed differences at the end of the experiment were due to baseline differences between the groups at the start of the experiment. The ideal way to ensure comparable groups is through completely random assignment to either the treatment or control group, which ensures that any characteristics which might influence the outcome will be randomly distributed between the two groups. The key characteristic of all experiments is manipulation by the researcher; common terms for this manipulation include treatment, stimulus, or intervention. In short, this manipulation is the experiment it is what the researcher believes to be the cause of the outcome of interest. Familiar examples include using an innovative teaching technique with one group of students, showing a new advertisement to one group of consumers, or providing preventive health information to one group of at-risk individuals. 4.2 Concept of Experimental Design Experimental design is a way to carefully plan experiments in advance so that your results are both objective and valid. The terms “Experimental Design” and “Design of Experiments” are used interchangeably and mean the same thing. Experimental research is any research conducted with a scientific approach, where a set of variables are kept constant while the other set of variables are CU IDOL SELF LEARNING MATERIAL (SLM)

Experimental Design 53 being measured as the subject of experiment. There are times when you don’t have enough data to support your decisions. In such situations, you need to carry out experiments to discover the facts. Experimental research can gather a lot of data that can help you make better decisions. The simplest example of an experimental research is conducting a laboratory test. As long as research is being conducted under scientifically acceptable conditions, it qualifies as an experimental research. A true experimental research is considered to be successful only when the researcher confirms that a change in the dependent variable is solely due to the manipulation of the independent variable. Experimental research should establish a cause and effect of a phenomenon, i.e., effects are observed from an experiment due to the cause. As naturally, occurring event can be confusing for researchers to establish conclusions. Examples: Acme Medicine is conducting an experiment to test a new vaccine, developed to immunise people against the common cold. To test the vaccine, Acme has 1000 volunteers – 500 men and 500 women. The participants range in age from 21 to 70. Treatment Placebo Vaccine 500 500 In this design, the experimenter randomly assigned participants to one of two treatment conditions. They received a placebo or they received the vaccine. The same number of participants (500) was assigned to each treatment condition (although this is not required). The dependent variable is the number of colds reported in each treatment condition. If the vaccine is effective, participants in the “vaccine” condition should report significantly fewer colds than participants in the “placebo” condition. A completely randomised design relies on randomisation to control for the effects of lurking variables. Lurking variables are potential causal variables that were not included explicitly in the CU IDOL SELF LEARNING MATERIAL (SLM)

54 Research Methods and Statistics - I study. By randomly assigning subjects to treatments, the experimenter assumes that, on average, lurking variables will affect each treatment condition equally. So, any significant differences between conditions can fairly be attributed to the independent variable. 4.3 Concept of Independent Variables An independent variable is defines as the variable that is changed or controlled in a scientific experiment. It represents the cause or reason for an outcome. Independent variables are the variables that the experimenter changes to test their dependent variable. A change in the independent variable directly causes a change in the dependent variable. The effect on the dependent variable is measured and recorded. The independent variable is the variable the experimenter changes or controls and is assumed to have a direct effect on the dependent variable. Independent Variable Examples A scientist is testing the effect of light and dark on the behaviour of moths by turning a light on and off. The independent variable is the amount of light and the moth’s reaction is the dependent variable. In a study to determine the effect of temperature on plant pigmentation, the independent variable (cause) is the temperature, while the amount of pigment or colour is the dependent variable (the effect). 4.4 Concept of Dependent Variables The dependent variable is ‘dependent’ on the independent variable. As the experimenter changes the independent variable, the change in the dependent variable is observed and recorded. When you take data in an experiment, the dependent variable is the one being measured. Dependent Variable Examples A scientist is testing the effect of light and dark on the behaviour of moths by turning a light on and off. The independent variable is the amount of light and the moth’s reaction is the dependent variable. A change in the independent variable (amount of light) directly causes a change in the dependent variable (moth behaviour). CU IDOL SELF LEARNING MATERIAL (SLM)

Experimental Design 55 4.5 Experimental Research Design Experimental research studies generally require testing of hypothesis for causal relationship amongst the variables. Naturally, these types of research studies require procedures that should not only reduce the bias but also lead to inferences about causality. This leads to necessity for experimental designs. Experimental design develops a framework of experiments based on thumb rule or statistical procedures. 4.6 Need for Experimental Research Design To achieve the goal of process optimisation, to prevent, or to minimise the occurrence of defective product, a thorough understanding of the process behaviour under different sets of process conditions is needed. Planning an experiment so that conformation relevant to the problem on hand will be made available is known as: “Designing and Experiment”. Experience has shown that if the data collection is properly planned, organised, summarised and interpreted using statistical principles, one will be able to draw valid and meaningful conclusions from the results. The design of experiment was found to be an excellent tool of effecting engineering development, quality improvement, process optimisation as well as cost reduction. 4.7 Basic Principles of Experimental Research Design 1. Principle of Replication: Under this principle, emphasis is on doing the same experiment more than once. Researcher applies each treatment in many experimental units instead of one. By doing so, he increases the statistical accuracy. For example, it can get a more precise effect of the mean effect of any factor. 2. Principle of Randomisation: The principle of randomisation provides researcher protection against the effect of extraneous factor, when he undertakes any experiment. It provides the freedom of designing and planning the experiment in such a fashion that variations, caused by extraneous factors can all be combined together and termed as chance. CU IDOL SELF LEARNING MATERIAL (SLM)

56 Research Methods and Statistics - I 4.8 Types of Experimental Designs Experimental design is the basic framework or structure of an experiment on which the whole research work is focused. There are two broad classification of experimental designs: formal experimental designs and informal experimental designs. The formal experimental designs offer the researcher more control and use of precise statistical procedures for analysis of the study whereas informal experimental designs normally use less sophisticated form of statistical procedures for analysis. The important experimental designs are as follows: 1. Informal Experimental Designs (a) Before-and-without Control Design In such an experimental design, a set of single test group is selected and the dependent variable is measured prior to application of a specific treatment. Subsequently, treatment is introduced and dependent variable is again measured. Therefore, the interpretation would be that treatment produced the delta difference in the outcome of dependent variable. An example of this can be, say, to observe the level of bacteria in a public swimming pool, prior and after the chlorination treatment. The main difficulty in such a design is that there could be other extraneous variations while the treatment is being introduced. If we continue with the above example, it can so happen that while chlorination treatment is being applied there is a rain fall, which adds air borne bacteria with rain water into the swimming pool. (b) After-only with Control Design In this type of experimental design, two areas, viz., test area and control area, are selected. In such a design, the treatment is applied only to the test area. The dependent variable is measured in both the areas at the same time. This leads to possible elimination of extraneous variations. The impact of treatment is assessed by subtracting the value of dependent variable in the control area from the value obtained in the test area. CU IDOL SELF LEARNING MATERIAL (SLM)

Experimental Design 57 Therefore, it can be said that this experiment design is superior to before and after, without control design. Example: The basic assumption in such a design is that the two areas are identical with respect to their behaviour towards the phenomenon considered. If this assumption is not true, there is the possibility of extraneous variation entering into the treatment effect. However, data can be collected in such a design without the introduction of problems with the passage of time. In this respect, the design is superior to before-and-after without control design (c) Before-and-after with Control Design This design, in a way, is an improvement on the first design and also combines control features of the second design. In this experimental design, two areas are selected and dependent variable is measured in both for common time period prior to the treatment. Then, the treatment is applied only in the test area and the dependent variable is measured again in both the test and control areas for an identical time period after the introduction of treatment. The impact of treatment is determined by subtracting the delta change in the dependent variable obtained in the control area from the delta change achieved in the dependent variable in the test area. 2. Formal Experimental Designs (a) Completely Randomised Design (CR Design) This type of design involves the principle of replication and principle of randomisation. In a sense, this is the easiest possible experimental design and therefore the procedure of analysis is also CU IDOL SELF LEARNING MATERIAL (SLM)

58 Research Methods and Statistics - I simpler. The basic characteristics of a completely randomised design is that subjects are randomly assigned to experimental treatments. For example, if we have 8 patients and we wish to give medication to 4, on the basis of treatment A and other four under treatment B, the randomisation process provides the possible opportunity that the group of 4 patients be selected from a set of 8 and being treated by treatment A and treatment B. Analysis procedure required to analyse such design is called one-way analysis of variance. This design provides the greatest number of degrees of freedom to the error. Normally, this design is used when experimental areas are homogenous. Strictly speaking, when all possible variation due to uncontrollable experimental factors is included under chance variation, the design of experiment is known as completely randomised design. Advantages of Completely Randomised Design This design has following advantages: (i) Complete flexibility is possible. The number of replications can be varied at will from treatment to treatment. It is possible to utilise all the experimental data. (ii) Statistical analysis is easy even if number of replications are not same for all treatments. (iii) The analysis remains simple even when results from some units or treatments are rejected. The relative loss of information due to such rejection is smallest compared with any other design. (b) Randomised Block Design (RB Design) This is the most familiar and a very important design among all experimental designs. Apart from completely randomised design, it is the simplest design to construct and analysis is known as randomised block design. The term randomised block emanated from agronomic research wherein several variables or treatments are applied to different blocks of land to study the effect of replication on experimental effort, such as, yield of different types of sugarcane by using variable amounts of water to irrigate the fields. For example to determine the difference in output of various types of machines, we may be able to isolate the effect due to difference in efficiencies of works by assigning machines at random to randomly selected workers. The underlying idea in this kind of experiment is CU IDOL SELF LEARNING MATERIAL (SLM)

Experimental Design 59 to compare the effect of all treatments within a block of experimental set up by eliminating possible environmental effects. By comparing mean square of treatments by the means square of remainder, it can be determined by F test whether the treatments have any effect, regardless of the fact of possibility of a significant variation from block to block. Example: Suppose four different forms of a standardised test in statistics were given to each of five students (selected one from each of the five IQ blocks) and following are the scores which they obtained. If each student separately randomised the order in which he or she took the four tests (by using random numbers or some similar device), we refer to the design of this experiment as a RB design. The purpose of this randomisation is to take care of such possible extraneous factors (say as fatigue) or perhaps the experience gained from repeatedly taking the test. Advantages of Completely Randomised Experimental Design Such a design offers the following major advantages: (i) It provides a great degree of flexibility because any number of factors, types and replications may be used. CU IDOL SELF LEARNING MATERIAL (SLM)

60 Research Methods and Statistics - I (ii) Analysis of such a design through statistical methods is rather simple. This is so, even in cases when a number of replications for each factor type or if the experimental errors are not similar from type to type of this factor. (iii) Even when data are missing or rejected, the method or analysis is quite simple in completely randomised block design. The loss of information due to missing data is limited as compared to any other experimental design. Major drawback of this design is that it is suited when the number of treatments is small and experimental conditions are homogenous. When the number of treatments is larger, it is possible to select designs which are more efficient than the completely randomised design. Therefore, randomised designs are rarely used for field experiments where numbers of treatments are relatively larger. (c) Latin Square Design (LS Design) This experimental design also emerged out of agronomic experimentations and is extensively used where there is a need to eliminate the trend of soil fertility in two directions simultaneously. In such a design, data is classified in rows and columns according to different treatments and varieties and is organised in the form of a square which is called a Latin Space. The genesis of the term “Latin Square” came from a mathematical puzzle that was devised many years before such experiments came into being. In such a design, since there have to be as many replications as are treatments, the domain of experiment is divided into slots organised in a square in a manner that they are as many slots in each row as there are in each column. This number is also same as the number of treatments. These slots are then assigned to various treatments in a manner for each treatments occurs only once in each row and only once in each columns. This can be organised in a large number of ways. However, particular way in which any particular layout is done must be determined randomly. The major advantages of Latin Square Experimental Design over other such designs are: (i) The two way stratification of Latin Square design leads a better control of the variation than the completely randomised design or the randomised block design. (ii) The two way stratification leads to elimination of variation which often results in a small error mean square. CU IDOL SELF LEARNING MATERIAL (SLM)

Experimental Design 61 (iii) By and large, analysis is still simple. However, it may be slightly more complex than an analysis for randomised block design (iv) Analysis remains relatively simple with Latin Square design even if some of the data are missing. There are procedures available to analyse Latin Squares in cases one wishes to omit one or more treatments, rows or columns. A major drawback of Latin Square design may be that number of the treatments must be equal to the number of treatments of the rows and columns. Also when number of treatment is more than seven, Latin Square design hardly is ever utilised, due to complexity in number of permutations and combinations. (d) Factorial Design In recent times, with a view to improve rational foundation of a scientific experimentation, the factorial design has proved to be one of the useful developments. It allows the researcher to evaluate the combined effect of two or more variables when used simultaneously. It is considered that information obtained from. Factorial experiments are more complete than that which is obtained from a set of single factor experiments. This is due to that fact that factorial experiments allow the evaluation of interaction effects. An interaction effect is generally attributed in two or more combination of variables over and above those that can be predicted from the variables if considered alone. Major reasons for including several factors in one experiment are: (i) Understanding the overall effect of the factors economically by conducting one single experiment of moderate size. (ii) Enlarging the basis of inference on a single factor by testing it under graded conditions of other factors. (iii) Finding out the manner in which the effect of factors interacts with one another. These may not be entirely independent but emphasis can be made to vary with a degree of experimentation. CU IDOL SELF LEARNING MATERIAL (SLM)

62 Research Methods and Statistics - I 4.9 Advantages of Experimental Research The advantages of Experimental Research can be summarised as follows: 1. It provides researchers with a high level of control. By being able to isolate specific variables, it becomes possible to determine if a potential outcome is viable. Each variable can be controlled on its own or in different combinations to study what possible outcomes are available for a product, theory, or idea as well. This provides a tremendous advantage in an ability to find accurate results. 2. There is no limit to the subject matter or industry involved. Experimental research is not limited to a specific industry or type of idea. It can be used in a wide variety of situations. Teachers might use experimental research to determine if a new method of teaching or a new curriculum is better than an older system. Pharmaceutical companies use experimental research to determine the viability of a new product. 3. Experimental research provides conclusions that are specific. Because experimental research provides such a high level of control, it can produce results that are specific and relevant with consistency. It is possible to determine success or failure, making it possible to understand the validity of a product, theory, or idea in a much shorter amount of time compared to other verification methods. You know the outcome of the research because you bring the variable to its conclusion. 4. The results of experimental research can be duplicated. Experimental research is straightforward, basic form of research that allows for its duplication when the same variables are controlled by others. This helps to promote the validity of a concept for products, ideas, and theories. This allows anyone to be able to check and verify published results, which often allows for better results to be achieved, because the exact steps can produce the exact results. CU IDOL SELF LEARNING MATERIAL (SLM)

Experimental Design 63 5. Natural settings can be replicated with faster speeds. When conducting research within a laboratory environment, it becomes possible to replicate conditions that could take a long time so that the variables can be tested appropriately. This allows researchers to have a greater control of the extraneous variables which may exist as well, limiting the unpredictability of nature as each variable is being carefully studied. 6. Experimental research allows cause and effect to be determined. The manipulation of variables allows for researchers to be able to look at various cause-and- effect relationships that a product, theory, or idea can produce. It is a process which allows researchers to dig deeper into what is possible, showing how the various variable relationships can provide specific benefits. In return, a greater understanding of the specifics within the research can be understood, even if an understanding of why that relationship is present is not presented to the researcher. 7. It can be combined with other research methods. This allows experimental research to be able to provide the scientific rigor that may be needed for the results to stand on their own. It provides the possibility of determining what may be best for a specific demographic or population while also offering a better transference than anecdotal research can typically provide. 4.10 Disadvantages of Experimental Research The disadvantages of Experimental Research can be summarised as follows: 1. Results are highly subjective due to the possibility of human error. Because experimental research requires specific levels of variable control, it is at a high risk of experiencing human error at some point during the research. Any error, whether it is systemic or random, can reveal information about the other variables and that would eliminate the validity of the experiment and research being conducted. CU IDOL SELF LEARNING MATERIAL (SLM)

64 Research Methods and Statistics - I 2. Experimental research can create situations that are not realistic. The variables of a product, theory, or idea are under such tight controls that the data being produced can be corrupted or inaccurate, but still seem like it is authentic. This can work in two negative ways for the researcher. Firstly, the variables can be controlled in such a way that it skews the data toward a favourable or desired result. Secondly, the data can be corrupted to seem like it is positive, but because the real-life environment is so different from the controlled environment, the positive results could never be achieved outside of the experimental research. 3. It is a time-consuming process. For it to be done properly, experimental research must isolate each variable and conduct testing on it. Then combinations of variables must also be considered. This process can be lengthy and require a large amount of financial and personnel resources. Those costs may never be offset by consumer sales if the product or idea never makes it to market. If what is being tested is a theory, it can lead to a false sense of validity that may change how others approach their own research. 4. There may be ethical or practical problems with variable control. It might seem like a good idea to test new pharmaceuticals on animals before humans to see if they will work, but what happens if the animal dies because of the experimental research? Experimental research might be effective, but sometimes the approach has ethical or practical complications that cannot be ignored. Sometimes there are variables that cannot be manipulated as it should be so that results can be obtained. 5. Experimental research does not provide an actual explanation. Experimental research is an opportunity to answer a Yes or No question. It will either show you that it will work or it will not work as intended. One could argue that partial results could be achieved, but that would still fit into the “No” category because the desired results were not fully achieved. The answer is nice to have, but there is no explanation as to how you got to that answer. Experimental research is unable to answer the question of “Why” when looking at outcomes. CU IDOL SELF LEARNING MATERIAL (SLM)

Experimental Design 65 6. Extraneous variables cannot always be controlled. Although laboratory settings can control extraneous variables, natural environments provide certain challenges. Some studies need to be completed in a natural setting to be accurate. It may not always be possible to control the extraneous variables because of the unpredictability of Mother Nature. Even if the variables are controlled, the outcome may ensure internal validity, but do so at the expense of external validity. Either way, applying the results to the general population can be quite challenging in either scenario. 7. Participants can be influenced by their current situation. Human error is not just confined to the researchers. Participants in an experimental research study can also be influenced by extraneous variables. There could be something in the environment, such an allergy that creates a distraction. In a conversation with a researcher, there may be a physical attraction that changes the responses of the participant. Even internal triggers, such as a fear of enclosed spaces, could influence the results that are obtained. It is also very common for participants to “go along” with what they think a researcher wants to see instead of providing an honest response. 8. Manipulating variables is not necessarily an objective standpoint. For research to be effective, it must be objective. Being able to manipulate variables reduces that objectivity. Although there are benefits to observing the consequences of such manipulation, those benefits may not provide realistic results that can be used in the future. Taking a sample is reflective of that sample and the results may not translate over to the general population. 9. Human responses in experimental research can be difficult to measure. There are many pressures that can be placed on people, from political to personal, and everything in-between. Different life experiences can cause people to react to the same situation in different ways. Not only does this mean that groups may not be comparable in experimental research, but also makes it difficult to measure the human responses that are obtained or observed. CU IDOL SELF LEARNING MATERIAL (SLM)

66 Research Methods and Statistics - I 4.11 Summary Experimental research designs are also widely used in psychology, education, and the social sciences, and are considered the gold standard for evaluating causal hypotheses. Their logic as illustrated above is straightforward, though their actual execution can be quite challenging. First, all experimental research designs are based on comparison between two or more groups. These groups must be composed of subjects who are similar on all characteristics which might influence the outcome of interest; otherwise, it is impossible to rule out the possibility that any observed differences at the end of the experiment were due to baseline differences between the groups at the start of the experiment. The ideal way to ensure comparable groups is through completely random assignment to either the treatment or control group, which ensures that any characteristics which might influence the outcome will be randomly distributed between the two groups. The key characteristic of all experiments is manipulation by the researcher; common terms for this manipulation include treatment, stimulus, or intervention. In short, this manipulation is the experiment it is what the researcher believes to be the cause of the outcome of interest. Familiar examples include using an innovative teaching technique with one group of students, showing a new advertisement to one group of consumers, or providing preventive health information to one group of at-risk individuals. In each case, the researcher hypothesises that the manipulation applied to one group will be the cause of a different outcome relative to the unexposed (or control) group. Experimental research should establish a cause and effect of a phenomenon, i.e., effects are observed from an experiment due to the cause. As naturally, occurring event can be confusing for researchers to establish conclusions. For instance, if a cardiology student conducts research to understand the effect of food on cholesterol and derives that most heart patients are non-vegetarians or have diabetes. They are aspects (causes) which can result in a heart attack (effect). An independent variable is defines as the variable that is changed or controlled in a scientific experiment. It represents the cause or reason for an outcome. Independent variables are the variables CU IDOL SELF LEARNING MATERIAL (SLM)

Experimental Design 67 that the experimenter changes to test their dependent variable. A change in the independent variable directly causes a change in the dependent variable. The effect on the dependent variable is measured and recorded. The independent variable is the variable the experimenter changes or controls and is assumed to have a direct effect on the dependent variable. The dependent variable is ‘dependent’ on the independent variable. As the experimenter changes the independent variable, the change in the dependent variable is observed and recorded. When you take data in an experiment, the dependent variable is the one being measured. Experimental research studies generally require testing of hypothesis for causal relationship amongst the variables. Naturally, these types of research studies require procedures that should not only reduce the bias but also lead to inferences about causality. This leads to necessity for experimental designs. Experimental design develops a framework of experiments based on thumb rule or statistical procedures. 4.12 Key Words/Abbreviations  Experimental Design: Experimental research designs are also widely used in psychology, education and the social sciences.  Independent Variables: An independent variable is defines as the variable that is changed or controlled in a scientific experiment.  Dependent Variables: The dependent variable is the one being measured.  Experimental Research Design: Experimental research studies generally require testing of hypothesis for causal relationship amongst the variables.  Informal Experimental Designs: Experimental research studies generally require testing of hypothesis for causal relationship amongst the variables.  Formal Experimental Designs: This type of design involves the principle of replication and principle of randomisation. CU IDOL SELF LEARNING MATERIAL (SLM)

68 Research Methods and Statistics - I  Randomised Block Design: This is the most familiar and a very important design among all experimental designs.  Latin Square Design: This experimental design also emerged out of agronomic experimentations and is extensively used. 4.13 Learning Activity 1. You are required to prepare a report on “Significance of Independent Variables and Dependent Variables”. _________________________________________________________________ _________________________________________________________________ 2. You are suggested to build a team of six members and prepare live project on “Impact of Experimental Research Design”. _________________________________________________________________ _________________________________________________________________ 4.14 Unit End Exercises (MCQs and Descriptive) Descriptive Type Questions 1. Explain the concept of experimental design. 2. Discuss about concepts of independent variables. 3. Explain the concept of dependent variables. 4. Discuss impact of experimental research design. 5. Explain the need for experimental research design. 6. Discuss the basic principles of experimental research design. CU IDOL SELF LEARNING MATERIAL (SLM)

Experimental Design 69 7. Explain the various types of experimental designs. 8. Discuss advantages of experimental research. 9. Explain disadvantages of experimental research. 10. Explain various limitations of experimental designs. Multiple Choice Questions 1. Which of the following designs are also widely used in psychology, education, and the social sciences, and are considered the gold standard for evaluating causal hypotheses? (a) Experimental Research (b) Causal Research (c) Descriptive Research (d) All the above 2. Which of the following is defines as the variable that is changed or controlled in a scientific experiment? (a) Dependent Variable (b) Independent Variable (c) Proactive Variable (d) Inactive Variable 3. Which of the following is not the principle of Experimental Research Design? (a) Principle of Replication (b) Principle of Randomisation (c) Principle of Analysis (d) Both (a) and (b) 4. Which of the following is the type of experimental design? (a) Experimental Research Designs (b) Informal Experimental Designs (c) Formal Experimental Designs (d) Both (b) and (c) CU IDOL SELF LEARNING MATERIAL (SLM)

70 Research Methods and Statistics - I 5. Which of the following considers the advantages of Experimental Research? (a) It provides researchers with a high level of control (b) There is no limit to the subject matter or industry involved (c) Experimental research provides conclusions that are specific (d) All the above Answers: 1. (a), 2. (b), 3. (c), 4. (d), 5. (d) 4.15 References References of this unit have been given at the end of the book.  CU IDOL SELF LEARNING MATERIAL (SLM)

Research Process 71 UNIT 5 RESEARCH PROCESS Structure: 5.0 Learning Objectives 5.1 Introduction 5.2 Research Process 5.3 Research Problem Identification and Formulation 5.4 Selection and Formulation of a Research Problem 5.5 Features of Research Problems 5.6 Criteria for Selecting the Research Problem 5.7 Review of Literature 5.8 Objectives of Review of Literature 5.9 Steps in Writing Review of Literature 5.10 Need for Review of Literature 5.11 Purpose of Review of Literature 5.12 Hypothesis 5.13 Characteristics of Good Hypothesis 5.14 Types of Hypothesis 5.15 Formulation and Testing of Hypothesis CU IDOL SELF LEARNING MATERIAL (SLM)

72 Research Methods and Statistics - I 5.16 Summary 5.17 Key Words/Abbreviations 5.18 LearningActivity 5.19 Unit End Exercises (MCQs and Descriptive) 5.20 References 5.0 Learning Objectives After studying this unit, you will be able to:  Explain the process of research  Describe the criteria for selecting the research problem 5.1 Introduction The research process involves identifying, locating, assessing and analysing the information you need to support your research question, and then developing and expressing your ideas. These are the same skills you need any time you write a report, proposal, or put together a presentation. A deeper understanding of the process of research will help you identify the similar features that occur in the different fields and the variety in the purpose and approaches to some studies. Understanding the research process will help you understand the implication of deviating from a systematic approach to research, as well as the associating consequences of ineffective and ineffectual research. Adopting the proposed model by Rummel and Ballaine (1963), there are six steps involved in the research process. These include identifying the area of study, choosing the topic, formulating a research plan, collecting and then analysing the data and then finally writing up the study. These steps can be represented in three phases, namely the planning phase and the research phase and then finally the presentation phase. 5.2 Research Process Research process involves execution of a series of phases towards accomplishment of the objectives of research. Each phase in the research process need not be carried out in a sequential process. Some of the phases can be carried out simultaneously. One should remember that the CU IDOL SELF LEARNING MATERIAL (SLM)

Research Process 73 various steps involved in research are not mutually exclusive; nor separate and distinct. They do not necessarily follow each other in any specific order and the researcher has to be constantly anticipating at each step in the research process the requirements of the subsequent steps. However, the idea of sequence will be useful for developing and carrying out research study in a systematic manner. The research process consists of the following distinctive interrelated phases: Step 1: Defining the Research Problem A problem need not necessarily mean that something is wrong in the current situation which needs to be rectified immediately. It simply indicates an issue for which finding a solution could help to improve an existing situation. Problem can be defined as any situation where a gap exists between the actual and the desired state. Problem statement or problem definition refers to a clear, precise and brief statement of question or issue that is to be investigated with the goal of finding a solution. Components of Research Problem The components of research problem are as suggested by R.L. Ackoff in the “Design of Social Research” is elaborated below: (i) There must be an individual or a group which has some difficulty with problem. (ii) There must be some objective(s) to be attained at. (iii) There must be alternative means or course of action for obtaining the objectives. (iv) There must be some doubt in the minds of a researcher with regard to the selection of alternatives. (v) There must be some environment to which the difficulty pertains. Criteria for Selecting the Research Problem The following criteria can be kept in the mind of researchers in selecting the research problem: (i) Subjects on which the research is carried on amply should not be normally chosen as there will not be a new dimension to reveal. (ii) Too narrow or too vague problems should be avoided. CU IDOL SELF LEARNING MATERIAL (SLM)

74 Research Methods and Statistics - I (iii) The researcher should be familiar with the subject chosen for research. The researcher should have enough knowledge, qualification and training in the selected problem area. (iv) The resources needed to solve the problem in terms of time, money, efforts and manpower requirement should be taken into account before embarking on a problem. (v) The subject of research should be familiar and feasible so that related research material or sources of research can be obtained easily. (vi) The selection of a problem must be preceded by a preliminary study. Research problems trigger the research process. Defining the research problem is a critical activity. A thorough understanding of research problem is a must for achieving success in the research endeavour. Defining the research problem begins with identifying the basic dilemma that prompts the research. It can be further developed by progressively breaking down the original dilemma into more specific and focus oriented objectives. Five steps could be envisaged in the identification research problem: (i) Identifying the broad problem area (ii) Literature review (iii) Identifying the research question (iv) Refining the research question (v) Developing investigative questions. Step 2: Review of Literature Literature survey is the review of published and unpublished work from secondary sources in the area of interest to the researcher. The purpose of conducting literature survey at this stage is: (i) To document the studies relevant to the problem identified for research. (ii) To ensure that no variable that has been taken up in the past related studies is ignored. CU IDOL SELF LEARNING MATERIAL (SLM)

Research Process 75 (iii) To avoid conducting similar type of study and thereby stopping the researcher from investing his resources in terms of time and effort in a research venture which is already solved. (iv) To provide a good framework and a solid foundation to proceed further in the investigation. (v) To have a comprehensive theoretical framework from which hypothesis can be developed for testing. (vi) To enable to develop the problem statement in a precise and clear manner. (vii) To enhance the testability and replicability of the findings of the current research. (viii) To understand the research gap. (ix) To confirm the appropriateness of procedure by referring to similar studies conducted in the past. (x) To trace inconsistencies, contradictions and consistencies. (xi) To clear conceptualisation. (xii) To familiarise with methodology, research tools and statistical analysis. Step 3: Formulation of Hypothesis A proposition that can be verified to determine its reality is a hypothesis. Therefore, one can say that a hypothesis is a verifiable counterpart of a proposition. A hypothesis may be defined as a logically conjectured relationship between two or more variables, expressed in the form of a testable statement. Relationship is proposed by using a strong logical argumentation. This logical relationship may be part of theoretical framework of the study. Step 4: Developing the Research Design A research design is the specification of methods and procedures for acquiring the information needed to structure or to solve problems. It is an overall operational pattern or framework of the project that stipulates the information to be collected, the sources from which information can be collected the procedures for collection of information. In other words the researcher should consider: (i) the design technique, (ii) the type of data, (iii) the sampling methodology and procedures, and (iv) the schedule and the budget. CU IDOL SELF LEARNING MATERIAL (SLM)

76 Research Methods and Statistics - I A good research design ensures that the information obtained is relevant to the research problem in an objective and economical manner. The research design can be described as a master plan or model or blueprint for the conduct of investigation. Step 5: Collection of Data Data is the facts presented to the researcher from the study environment. Data can be gathered from a single location or from all over the world based on the research objectives and the resource allocation. The data collection method ranges from observation, questionnaires, laboratory notes and other modern instruments and devices. Data can be characterised by their abstractness, verifiability, elusiveness and closeness to the phenomenon. As abstractions, data are more metaphorical than real. When sensory experiences consistently produce the same result, then the data is said to be trustworthy as they are verified. Data capturing is elusive, complicated by the speed at which events occur and the time-bound nature of observation. Primary data can be collected either through experiment or through survey. If the researcher conducts an experiment, he observes some quantitative measurements, or the data, with the help of which he examines the truth contained in his hypothesis. But in the case of a survey, data can be collected by any one or more of the following ways: (i) By observation: This method implies the collection of information by way of investigator’s own observations, without interviewing the respondents. The information obtained relates to what is currently happening and is not complicated by either the past behaviour or future intentions or attitudes of respondents. This method is no doubt an expensive method and the information provided by this method is also very limited. As such this method is not suitable in inquiries where large samples are concerned. (ii) Through personal interview: The investigator follows a rigid procedure and seeks answers to a set of pre-conceived questions through personal interviews. This method of collecting data is usually carried out in a structured way where output depends upon the ability of the interviewer to a large extent. (iii) Through telephonicinterview: This method of collecting information involves contacting the respondents on telephone. This is not a very widely used method but it plays an important CU IDOL SELF LEARNING MATERIAL (SLM)

Research Process 77 role in industrial surveys in developed regions, particularly, when the survey has to be accomplished in a very limited time. (iv) By mailing of questionnaires: The researcher and the respondents do come in contact with each other if this method of survey is adopted. Questionnaires are mailed to the respondents with a request to return after completing the same. It is the most extensively used method in various economic and business surveys. Before applying this method, usually a Pilot Study for testing the questionnaire is conducted which reveals the weaknesses, if any, in the questionnaire. (v) Through schedules: Under this method, the enumerators are appointed and given training. They are provided with schedules containing relevant questions. These enumerators go to respondents with these schedules. Data are collected by filling up the schedules by enumerators on the basis of replies given by respondents. The researcher should select one of these methods of collecting the data taking into consideration the nature of investigation, objective and scope of the inquiry, financial resources, available time and the desired degree of accuracy. Though he should pay attention to all these factors, but much depends upon the ability and experience of the researcher. In this context Dr. A.L. Bowley very aptly remarks that “In collection of statistical data, commonsense is the chief requisite and experience the chief teacher”. Step 6: Data Analysis and Interpretation Research is conducted for the purpose of acquiring information. Raw data as such does not provide information. Further analysis needs to be done to obtain information out of data. Data analysis involves application of statistical techniques for reducing accumulated data to a manageable size leading to summaries. Responses acquired by way of administering questionnaires should be subjected to analysis so as to ascertain the behaviour of variables, the relationship between variables, etc. Analysis should be focused to find answers to research questions/hypothesis. Various statistical softwares are available to make the job of data analysis easier. However, interpretation needs to be made with expertise as the recommendations are based on them. CU IDOL SELF LEARNING MATERIAL (SLM)

78 Research Methods and Statistics - I Analysis of data requires a number of closely related operations such as establishment of categories, the application of these categories to raw data through coding, tabulation and then drawing statistical inferences. The unwieldy data should necessarily be condensed into a few manageable groups and tables for further analysis. Thus, researcher should classify the raw data into some purposeful and usable categories. Coding operation is usually done at this stage through which the categories of data are transformed into symbols that may be tabulated and counted. Editing is the procedure that improves the quality of data for coding. With coding, the stage is ready for tabulation. Tabulation is a part of the technical procedure wherein the classified data are put in the form of tables. The mechanical devices can be made use of at this juncture. A great deal of data, especially in large inquiries, is tabulated by computers. Computers not only save time but also make it possible to study large number of variables affecting a problem simultaneously. Analysis work after tabulation is generally based on the computation of various percentages, coefficients, etc. by applying various well defined statistical formulae. In the process of analysis, relationships or differences supporting or conflicting with original or new hypotheses should be subjected to tests of significance to determine with what validity data can be said to indicate any conclusion(s). If a hypothesis is tested and upheld several times, it may be possible for the researcher to arrive at generalisation, i.e., to build a theory. Step 7: Research Reporting It is only through reports the researcher communicates about the research work, findings and recommendations to the outside world. The report has to be prepared in the style that will be understood by the target audience. The type of report varies depending on the type of research, length of report and the purpose. The researcher should take care to see that the report addresses all the objectives of research in a lucid manner. The report should be adapted to the needs of the target audience and care must be taken to use appropriate words in projecting the interpretation, recommendations and conclusion. Areport should contain an executive summary consisting of synopsis of problem, findings and recommendations. It should speak about the background of the study, the statement of the problem, literature summary, methods and procedures, findings, recommendations and conclusion CU IDOL SELF LEARNING MATERIAL (SLM)

Research Process 79 The layout of the report should be as follows: (i) the preliminary pages; (ii) the main text and (iii) the end matter. In its preliminary pages, the report should carry study title acknowledgements declarations and foreword. Then there should be a table of contents followed by a list of tables and list of graphs and charts, if any, given in the report. The main text of the report should have the following parts: (a) Introduction: It should contain a clear statement of the objective of the research and an explanation of the methodology adopted in accomplishing the research. The scope of the study along with various limitations should as well be stated in this part. (b) Summary of findings: After introduction there would appear a statement of findings and recommendations in non-technical language. If the findings are extensive, they should be summarised. (c) Main report: The main body of the report should be presented in a logical sequence and broken down into readily identifiable sections. (d) Conclusion: Towards the end of the main text, researcher should again put down the results of his research clearly and precisely. In fact, it is the final summing up. At the end of the report, appendices should be enlisted in respect of all technical data. References/ Bibliography, i.e., list of books, journals, reports, etc. References should also be given in the end. Index should also be given specially in a published research report. Report should be written in a concise and objective style in simple language avoiding vague expressions such as ‘it seems,’ ‘there may be’, and the like. Charts and illustrations in the main report should be used only if they present the information more clearly and forcibly. Calculated ‘confidence limits’ must be mentioned and the various constraints experienced in conducting research operations may as well be stated. CU IDOL SELF LEARNING MATERIAL (SLM)

80 Research Methods and Statistics - I 5.3 Research Problem Identification and Formulation A research problem is a statement regarding an area of concern, a circumstance to be improved upon, a difficulty to be eliminated or a troubling question that exists in scholarly literature, in theory or in practice that point to the need for meaningful understanding and deliberate investigation. In some social science disciplines, the research problem is typically posed in the form of one or more questions. A research problem does not state how to do something, offer a vague or broad proposition or present a value question. Meaning of Research Problem Research problem refers to the situation where a gap exists between the actual and the desired state. The problem can be generated either by an initiating idea or by a perceived problem area. Example: Investigation of ‘rhythmic patterns in settlement planning’ is the product of an idea that there are such things as rhythmic patterns in settlement plans, even if no one has detected them before. This kind of idea will then need to be formulated more precisely in order to develop it into a researchable problem. We are surrounded by problems connected with society, the built environment, education, etc., many of which can readily be perceived. 5.4 Selection and Formulation of a Research Problem An adequate concept of the problem is one of the most important aspects of research. Problems in social science research are questions about the state of affairs in the field. Whereas different types of research problems exist, all ask questions to which research respond in form of a scientific answer. A problem is ‘an interrogative sentence or statement that asks about the relationships existing between two or more variables’. The answer is what is being sought in the research. It is however, to be noted that a distinction is commonly made in the characteristics of problems between the different kinds of research. A problem in both experimental and ex-post-facto research involves a question about the relation that exists between two or more variables. For instance, let us consider the problem: The impacts of river basin development on production performance of peasant farmers. CU IDOL SELF LEARNING MATERIAL (SLM)

Research Process 81 A problem need not necessarily mean that something is wrong in the current situation which needs to be rectified immediately. It simply indicates an issue for which finding a solution could help to improve an existing situation. Problem statement or problem definition refers to a clear, precise and succinct statement of question or issue that is to be investigated with the goal of finding an answer or solution. 5.5 Features of Research Problems Various important features of research problems are: (i) It should be of great interest to the researcher. Researcher shall have to spend many months investigating the problem. Alively interest in the subject will be an invaluable incentive to persevere. (ii) The problem should be significant. It is not worth time and effort investigating a trivial problem or repeating work that has already been done elsewhere. (iii) The problem should be delineated. Consider the time researcher have to complete the work, and the depth to which the problem will be addressed. Researcher can cover a wide field only superficially, and the more researchers restrict the field, the more detailed the study can be. Researcher should also consider the cost of necessary travel and other expenses. (iv) Researcher should be able to obtain the information required. Researcher cannot carry out research if researcher fail to collect the relevant information needed to tackle researcher problem, either because researcher lack access to documents or other sources, and/or because researcher have not obtained the cooperation of individuals or organisations essential to the research. (v) Researcher should be able to draw conclusions related to the problem. The point of asking a question is to find an answer. The problem should be one to which the research can offer some solution, or at least the elimination of some false ‘solutions’. (vi) Researcher should be able to state the problem clearly and concisely. A precise, well thought out and fully articulated sentence, understandable by anyone, should normally clearly be able to explain just what the problem is. CU IDOL SELF LEARNING MATERIAL (SLM)

82 Research Methods and Statistics - I 5.6 Criteria for Selecting the Research Problem The following criteria can be kept in the minds of researchers in selecting the research problem: (i) Subjects on which the research is carried on amply should not be normally chosen as there will not be a new dimension to reveal. (ii) Too narrow or too vague problems should be avoided. (iii) The researcher should be familiar with the subject chosen for research. The researcher should have enough knowledge, qualification and training in the selected problem area. (iv) The resources needed to solve the problem in terms of time, money, efforts, manpower requirement should be taken into account before embarking on a problem. (v) The subject of research should be familiar and feasible so that related research material or sources of research can be obtained easily. (vi) The selection of a problem must be preceded by a preliminary study. Research problems trigger the research process. Defining the research problem is a critical activity. A thorough understanding of research problem is a must for achieving success in the research endeavour. Defining the research problem begins with identifying the basic dilemma that prompts the research. It can be further developed by progressively breaking down the original dilemma into more specific and focus oriented objectives. Five steps could be envisaged: 1. Identifying the broad problem area 2. Literature review 3. Identifying the research question 4. Refining the research question 5. Developing investigative questions. CU IDOL SELF LEARNING MATERIAL (SLM)

Research Process 83 5.7 Review of Literature Review of Literature is a description of the literature relevant to a particular field or topic. It gives an overview of what has been said, who the key writers are, what are the prevailing theories and hypotheses, what questions are being asked and what methods and methodologies are appropriate and useful. As such, it is not in itself primary research but rather it reports on other findings. Definition of Review of Literature According to Cooper, H.M., “Literature review uses as its database reports of primary or original scholarship and does not report new primary scholarship itself. The primary reports used in the literature may be verbal, but in the vast majority of cases reports are written documents. The types of scholarship may be empirical, theoretical, critical/analytic or methodological in nature. Second a literature review seeks to describe, summarise, evaluate, clarify and/or integrate the content of primary reports.” 5.8 Objectives of Review of Literature The following are the objectives of review of literature: (a) To provide a good framework and a solid foundation to proceed further in the investigation. (b) To have a comprehensive theoretical framework from which hypothesis can be developed for testing. (c) To enable to develop the problem statement in a precise and clear manner. (d) To document the studies relevant to the problem identified for research. (e) To ensure that no variable that has been taken up in the past related studies is ignored. (f) To avoid conducting similar type of study and thereby stopping the researcher from investing his resources in terms of time and effort in a research venture which is already solved. (g) To understand the research gap. (h) To stimulate the researcher to carry out the work. CU IDOL SELF LEARNING MATERIAL (SLM)

84 Research Methods and Statistics - I (i) To confirm the appropriateness of procedure by referring to similar studies conducted in the past. (j) To trace inconsistencies, contradictions and consistencies. 5.9 Steps in Writing Review of Literature Various steps in writing Review of Literature are: Step 1: Identifying the Sources The data can be obtained from the library by going through books, journals, newspapers, magazines, conference proceedings, doctoral dissertation, thesis, government publications and other reports. Computerised databases include bibliographies, abstract and full text of articles. Bibliographic databases display only the bibliographic citations, i.e., the name of the author, the title of the article/ journal, source of publication, year, volume and page numbers. The abstract databases in addition to the above said information provides an abstract or summary of the article. The full-text databases as the name suggests, enables to download the full text of the article. Step 2: Gathering Relevant Information The articles gathered either from books, journal or online sources could as such act as a reservoir of information. These sources could lead to further information through the citation and references used. The list of journals and references referred in the articles could lead us further to the source of information. Also during the course of reading the articles, the researcher can get insight into new variables or new avenues hitherto unexplored. Step 3: Presenting the Review of Literature The literature should be presented in a clear and logical manner citing the author, year of study, objectives of the research, major findings and implications. The researcher should present the literature in a chronological order and in a coherent manner. There are several methods of citing references in the literature. CU IDOL SELF LEARNING MATERIAL (SLM)

Research Process 85 5.10 Need for Review of Literature 1. Jump offs: Start with handbooks and research overviews and review their references. 2. Track and map authors: Track the names of key authors and locate their original works. 3. Record key definitions and their context: Look for patterns and frameworks in what is written about a topic such as the context – social, political and historical. 4. Establish a personal search pattern: Determine types of materials needed (books, primary sources, government documents, statistics, scholarly articles, opinion pieces, etc.) and how to access them. Become aware of your search patterns. Track your strategy including reference tools, databases, authors, questions and search problems. 5. Make strategic use of journal index and search engine advanced search capabilities: Work out the best way to search each journal index along with Google and Google Scholar. List search terms, subjects and descriptors which are specific to each index. Find out how to narrow searches. Search key authors. 6. Use citation indexes: Search key authors and specific works in a citation index to find who has cited them. See Web of Science; Google Scholar. 7. Track your references: Use Reference Works to manage references and follow the APA style of referencing. 8. Use library guides if appropriate: See http://library.queensu.ca/research/subjects. Use the EDUC890 handout under Faculty/graduates to get started on your research: http:// library.queensu.ca/webedu. 5.11 Purpose of Review of Literature A literature review is an evaluative report of studies found in the literature related to your selected area. The review should describe, summarise, evaluate and clarify this literature. It should give a theoretical basis for the research and help you determine the nature of your own research. Select a limited number of works that are central to your area rather than trying to collect a large number of works that are not as closely connected to your topic area. CU IDOL SELF LEARNING MATERIAL (SLM)

86 Research Methods and Statistics - I A literature review goes beyond the search for information and includes the identification and articulation of relationships between the literature and your field of research. While the form of the literature review may vary with different types of studies, the basic purposes remain constant: (i) Provide a context for the research. (ii) Justify the research. (iii) Ensure the research hasn't been done before (or that it is not just a “replication study”). (iv) Show where the research fits into the existing body of knowledge. (v) Enable the researcher to learn from previous theory on the subject. (vi) Illustrate how the subject has been studied previously. (vii) Highlight flaws in previous research. (viii) Outline gaps in previous research. (ix) Show that the work is adding to the understanding and knowledge of the field. (x) Help refine, refocus or even change the topic. 5.12 Hypothesis Hypothesis is a statement of expectation or prediction that will be tested by research. This is a tentative statement about the relationship between two or more variables. Research hypothesis is a specific, testable prediction about what you expect to happen in your study. The hypothesis is generated via a number of means, but is usually the result of a process of inductive reasoning where observations lead to the formation of a theory. Scientists then use a large battery of deductive methods to arrive at a hypothesis that is testable, falsifiable and realistic. The research hypothesis is a paring down of the problem into something testable and falsifiable. In the aforementioned example, a researcher might speculate that the decline in the fish stocks is due to prolonged over fishing. Scientists must generate a realistic and testable hypothesis around which they can build the experiment. CU IDOL SELF LEARNING MATERIAL (SLM)

Research Process 87 A hypothesis must be testable, taking into account current knowledge and techniques, and be realistic. If the researcher does not have a multi-million dollar budget then there is no point in generating complicated hypotheses. A hypothesis must be verifiable by statistical and analytical means, to allow a verification or falsification. In fact, a hypothesis is never proved, and it is better practice to use the terms ‘supported’ or ‘verified’. This means that the research showed that the evidence supported the hypothesis and further research is built upon that. A research hypothesis, which stands the test of time, eventually becomes a theory, such as Einstein’s General Relativity. Even then, as with Newton’s Laws, they can still be falsified or adapted. Definitions of Hypothesis According to Kerlinger (1956), “A hypothesis is a conjectural statement of the relation between two or more variables”. According to Eric Rogers (1966), “Hypotheses are single tentative guesses, good hunches assumed for use in devising theory or planning experiments intended to be given a direct experimental test when possible”. According to Creswell (1994), “Hypothesis is a formal statement that presents the expected relationship between an independent and dependent variable.” 5.13 Characteristics of Good Hypothesis The characteristics of a good hypothesis can be summarised as follows: 1. Simple to Understand A hypothesis should be so dabble to every layman, P.V young says, “A hypothesis would be simple, if a researcher has more in sight towards the problem”. W-ocean stated that “A hypothesis should be as sharp as razor’s blade”. So, a good hypothesis must be simple and have no complexity. CU IDOL SELF LEARNING MATERIAL (SLM)

88 Research Methods and Statistics - I 2. Conceptually Clear A hypothesis must be conceptually clear. It should be clear from ambiguous information. The terminology used in it must be clear and acceptable to everyone. 3. Testability A good hypothesis should be tested empirically. It should be stated and formulated after verification and deep observation. Thus testability is the primary feature of a good hypothesis. 4. Relevant to Problem If a hypothesis is relevant to a particular problem, it would be considered as good one. A hypothesis is guidance for the identification and solution of the problem. So, it must be accordance to the problem. 5. Power of Prediction One of the valuable attribute of a good hypothesis is to predict for future. It not only clears the present problematic situation but also predict for the future that what would be happened in the coming time. So, hypothesis is a best guide of research activity due to power of prediction. 6. Closest to Observable Things A hypothesis must have close contact with observable things. It does not believe on air castles but it is based on observation. Those things and objects which we cannot observe, for that hypothesis cannot be formulated. The verification of a hypothesis is based on observable things. 7. Specific Problem It should be formulated for a particular and specific problem. It should not include generalisation. If generalisation exists, then a hypothesis cannot reach to the correct conclusions. 8. Relevant to Available Techniques Hypothesis must be relevant to the techniques which is available for testing. A researcher must know about the workable techniques before formulating a hypothesis. CU IDOL SELF LEARNING MATERIAL (SLM)

Research Process 89 9. Fruitful for New Discoveries It should be able to provide new suggestions and ways of knowledge. It must create new discoveries of knowledge J.S. Mill, one of the eminent researcher says that “Hypothesis is the best source of new knowledge it creates new ways of discoveries”. 10. Consistency and Harmony Internal harmony and consistency is a major characteristic of good hypothesis. It should be out of contradictions and conflicts. There must be a close relationship between variables which one is dependent on other. 5.14 Types of Hypothesis 1. Descriptive Hypothesis Descriptive hypothesis contains only one variable thereby it is also called as univariate hypothesis. Descriptive hypotheses typically state the existence, size, form or distribution of some variable. The first hypothesis contains only one variable. It only shows the distribution of the level of commitment among the officers of the organisation which is higher than average. Such a hypothesis is an example of a Descriptive Hypothesis. Researchers usually uses research questions rather than descriptive hypothesis. For example, what is the level of commitment of officers in your organisation? 2. Relational Hypothesis These are the propositions that describe a relationship between two variables. The relationship could be non-directional or directional, positive or negative, causal or simply correlation. While stating the relationship between the two variables, if the terms of positive, negative, more than or less than is used then such hypotheses are directional because the direction of the relationship between the variables has been indicated. These hypotheses are relational as well as directional. The directional hypothesis is the one in which the direction of the relationship has been specified. The relationship may be very strong but whether it is positive or negative has not been postulated. CU IDOL SELF LEARNING MATERIAL (SLM)

90 Research Methods and Statistics - I 3. Correlational Hypothesis These state merely that the variables occur together in some specified manner without implying that one causes the other. Such weak claims are often made when we believe that there are more basic causal forces that affect both variables. For example, level of job commitment of officers is positively associated with their level of efficiency. Here, we do not make any claim that one variable causes the other to change. That will be possible only if we have control on all other factors that could influence our dependent variable. 4. Explanatory (Causal) Hypothesis This implies the existence of, or a change in, one variable causes or leads to a change in the other variable. This brings in the notions of independent and the dependent variables. Cause means to “help make happen.” So, the independent variable may not be the sole reason for the existence of or change in the dependent variable. The researcher may have to identify the other possible causes and control their effect in case the causal effect of independent variable has to be determined on the dependent variable. This may be possible in an experimental design of research. 5. Null Hypothesis It is used for testing the hypothesis formulated by the researcher. Researchers treat evidence that supports a hypothesis differently from the evidence that opposes it. They give negative evidence more importance than to the positive one. It is because the negative evidence tarnishes the hypothesis. It shows that the predictions made by the hypothesis are wrong. The null hypothesis simply states that there is no relationship between the variables or the relationship between the variables is “zero.” It does not take into consideration the direction of association, which may be a second step in testing the hypothesis. First, we look whether or not there is an association then we go for the direction of association and the strength of association. Experts recommend that we test our hypothesis indirectly by testing the null hypothesis. In case we have any credibility in our hypothesis, then the CU IDOL SELF LEARNING MATERIAL (SLM)

Research Process 91 research data should reject the null hypothesis. Rejection of the null hypothesis leads to the acceptance of the alternative hypothesis. 6. Alternative Hypothesis The alternative (to the null) hypothesis simply states that there is a relationship between the variables under study. In our example it could be: There is a relationship between the level of job commitment and the level of efficiency. Not only there is an association between the two variables under study but also the relationship is perfect which is indicated by the number “1”. There is a relationship between the level of job commitment of officers and their level of efficiency. 5.15 Formulation and Testing of Hypothesis Formulating a hypothesis helps by defining an initial explanation to be tested in the research process. A proposition that can be verified to determine its reality is a hypothesis. Therefore, one can say that a hypothesis is a verifiable counterpart of a proposition. A hypothesis may be defined as a logically conjectured relationship between two or more variables, expressed in the form of a testable statement. Relationship is proposed by using a strong logical argumentation. This logical relationship may be part of theoretical framework of the study. Both quantitative and qualitative research involves formulating a hypothesis to address the research problem. Hypotheses that suggest a causal relationship involve at least one independent variable and at least one dependent variable; in other words, one variable which is presumed to affect the other. An independent variable is one whose value is manipulated by the researcher or experimenter. A dependent variable is a variable whose values are presumed to change as a result of changes in the independent variable. Formulation of hypothesis is an assumption or suggested explanation about how two or more variables are related. It is a crucial step in the scientific method and, therefore, a vital aspect of all scientific research. There are no definitive guidelines for the production of new hypotheses. The CU IDOL SELF LEARNING MATERIAL (SLM)

92 Research Methods and Statistics - I history of science is filled with stories of scientists claiming a flash of inspiration, or a hunch, which then motivated them to look for evidence to support or refute the idea. 5.16 Summary The research process involves identifying, locating, assessing, and analysing the information you need to support your research question, and then developing and expressing your ideas. These are the same skills you need any time you write a report, proposal, or put together a presentation. A deeper understanding of the process of research will help you identify the similar features that occur in the different fields and the variety in the purpose and approaches to some studies. Understanding the research process will help you understand the implication of deviating from a systematic approach to research, as well as the associating consequences of ineffective and ineffectual research. Adopting the proposed model by Rummel and Ballaine (1963), there are six steps involved in the research process. These include identifying the area of study, choosing the topic, formulating a research plan, collecting and then analysing the data and then finally writing up the study. These steps can be represented in three phases, namely the planning phase and the research phase and then finally the presentation phase. A proposition that can be verified to determine its reality is a hypothesis. Therefore one can say that a hypothesis is a verifiable counterpart of a proposition. A hypothesis may be defined as a logically conjectured relationship between two or more variables, expressed in the form of a testable statement. Relationship is proposed by using a strong logical argumentation. This logical relationship may be part of theoretical framework of the study. A research design is the specification of methods and procedures for acquiring the information needed to structure or to solve problems. It is an overall operational pattern or framework of the project that stipulates the information to be collected, the sources from which information can be collected the procedures for collection of information. In other words, the researcher should consider (i) the design technique, (ii) the type of data, (iii) the sampling methodology and procedures, and (iv) the schedule and the budget. CU IDOL SELF LEARNING MATERIAL (SLM)

Research Process 93 Research is conducted for the purpose of acquiring information. Raw data as such does not provide information. Further analysis needs to be done to obtain information out of data. Data analysis involves application of statistical techniques for reducing accumulated data to a manageable size leading to summaries. Responses acquired by way of administering questionnaires should be subjected to analysis so as to ascertain the behaviour of variables, the relationship between variables, etc. A research problem is a statement regarding an area of concern, a circumstance to be improved upon, a difficulty to be eliminated or a troubling question that exists in scholarly literature, in theory or in practice that point to the need for meaningful understanding and deliberate investigation. In some social science disciplines, the research problem is typically posed in the form of one or more questions. A research problem does not state how to do something, offer a vague or broad proposition or present a value question. Review of Literature is a description of the literature relevant to a particular field or topic. It gives an overview of what has been said, who the key writers are, what are the prevailing theories and hypotheses, what questions are being asked and what methods and methodologies are appropriate and useful. As such, it is not in itself primary research but rather it reports on other findings. 5.17 Key Words/Abbreviations  Research Process: The research process involves identifying, locating, assessing, and analysing the information.  Research Problem: A problem need not necessarily mean that something is wrong in the current situation which needs to be rectified immediately.  Review of Literature: Literature survey is the review of published and unpublished work from secondary sources in the area of interest to the researcher.  Hypothesis Building: Hypothesis is a statement of expectation or prediction that will be tested by research. CU IDOL SELF LEARNING MATERIAL (SLM)

94 Research Methods and Statistics - I  Descriptive Hypothesis: Descriptive hypothesis contains only one variable thereby it is also called as univariate hypothesis.  Relational Hypothesis: These are the propositions that describe a relationship between two variables.  Correlational Hypothesis: These state merely that the variables occur together in some specified manner without implying that one causes the other.  Null Hypothesis: It is used for testing the hypothesis formulated by the researcher.  Alternative Hypothesis: The alternative (to the null) hypothesis simply states that there is a relationship between the variables under study. 5.18 Learning Activity 1. You are required to identify various steps in research process and prepare project report based on the steps. _________________________________________________________________ _________________________________________________________________ 2. You are suggested to identify various types of Null Hypothesis and their implementations for empirical research study. _________________________________________________________________ _________________________________________________________________ 5.19 Unit End Exercises (MCQs and Descriptive) Descriptive Type Questions 1. Explain various steps in Research process. 2. Discuss Research problem identification and formulation. CU IDOL SELF LEARNING MATERIAL (SLM)