Research design

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Research Design, Types of Research design, Experimental error, Experimental design, randomization,replication and local control.

Research Design, Types of Research design, Experimental error, Experimental design, randomization,replication and local control.

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  • 2. Research Design  Decisions regarding what, where, when, how much, by what means concerning an inquiry or a research study constitute a research design.  The research design is the master plan specifying the methods and procedures for collecting and analyzing the needed information.  Design includes an outline of what the researcher will do from writing the hypothesis and its operational implications to the final analysis of data
  • 3. Research design should answer (i) What is the study about? (ii) Why is the study being made? (iii) Where will the study be carried out? (iv) What type of data is required? (v) Where can the required data be found? (vi) What periods of time will the study include? (vii) What will be the sample design? (viii) What techniques of data collection will be used? (ix) How will the data be analyzed? (x) In what style will the report be prepared?
  • 4. Research Design (by considering all previous questions) Research Design Statistical design ( no of item, gathering info) Observational design (Observational condition) Sample design (Method of selecting item for study) Operational design (techniques)
  • 5. Research Design  Sample design: this deals with the technique of selecting items and thus requires careful observation for the given research study.  Observational design: this relates to the conditions under which the experiments are to be conducted.  Statistical design: this concerns the question of how many items are to be observed, and how are the collected data and information going to be analyzed.  Operational design: this deals with the methods by which the procedures specified in the sample, observational and statistical designs can be
  • 6. Need of Research Design  It facilitates smooth sailing of various research operation.  It makes research efficient as possible yielding, maximum information with minimal expenditure of effort ,time and money.  Eg . In house building ,we require map or design of house. Similarly we require research design for data collection and analysis of data of our research project
  • 7. Features of good research design  Design which should Minimize bias Maximizes reliability of data collected Maximize the reliability of data analyzed Minimum experimental error (human error, mistakes in data entry, mistakes in design of experiment and random error)
  • 8. Research design must, at least, contain (a) a clear statement of the research problem; (b) procedures and techniques to be used for gathering information; (c) the population to be studied; (d) methods to be used in processing and analyzing data
  • 9. Some concepts relating to design  Variable : A variable is any characteristics, number, or quantity that can be measured or counted. Ex: Age, sex, business income and country Birth
  • 10. Quantitative variable  Numeric variables have values that describe a measurable quantity as a number, like 'how many' or 'how much'. Therefore numeric variables are quantitative variables. A continuous variable is a numeric variable. Observations can take any value between a certain set of real numbers. Ex: time, height, temperature etc. A discrete variable is a numeric variable. Observations can take a value based on a count from a set of distinct whole values. Ex : number of children's in family, number of students in class etc
  • 11. Qualitative Variable  Categorical variables have values that describe a 'quality' or 'characteristic' of a data unit, like 'what type' or 'which category’. Therefore, categorical variables are qualitative variables. An ordinal variable is a categorical variable. Observations can take a value that can be logically ordered or ranked. Ex : academic grades (i.e. A, B, C), clothing size (i.e. small, medium, large, extra large) . A nominal variable is a categorical variable. Observations can take a value that is not able to be organized in a logical sequence. Ex: sex, eye color, religion.
  • 12. Extraneous variable  Extraneous Variables are undesirable variables that influence the relationship between the variables that an experimenter is examining. For example : if you want to measure the relationship between student working hours and exam performances. Student intelligence play as a one of the extraneous variable in this study.  Whatever effect is noticed on dependent variable as a result of extraneous variable(s) is technically described as an ‘experimental error’.
  • 13. Control and Confounded  Control: One important characteristic of a good research design is to minimize the influence or effect of extraneous variable(s).  Confounded relationship: When the dependent variable is not free from the influence of extraneous variable(s), the relationship between the dependent and independent variables is said to be confounded by an extraneous variable(s).
  • 14. Scientific Method  The scientific method is a body of techniques for investigating phenomena, acquiring new knowledge, or correcting and integrating previous knowledge
  • 15. Research Hypothesis  A research hypothesis is the statement created by researchers when they speculate upon the outcome of a research or experiment.  When a prediction or a hypothesized relationship is to be tested by scientific methods, it is termed as research hypothesis.  The research hypothesis is a predictive statement that relates an independent variable to a dependent variable. Ex: listening music lowers blood pressure level.
  • 16. Experimental and non-experimental hypothesis-testing research  Experimental and non-experimental hypothesis-testing research: When the purpose of research is to test a research hypothesis, it is termed as hypothesis-testing research. It can be of the experimental design or of the non-experimental design.  Research in which the independent variable is manipulated is termed ‘experimental hypothesis-testing research’  Research in which an independent variable is not manipulated is called ‘non-experimental hypothesis-testing research’.  For instance, suppose a researcher wants to study whether intelligence affects reading ability for a group of students. he randomly selects 50 students and tests their intelligence and reading ability by calculating the coefficient of correlation between the two sets of scores. (NE Hypothesis testing)  researcher randomly selects 50 students from a group of students who are to take a course in statistics and then divides them into two groups by randomly assigning 25 to Group A, the usual studies programme, and 25 to Group B, the special studies programme. At the end of the course, he administers a test to each group in order to judge the effectiveness of the training programme on the student’s performance-level. (E Hypothesis testing) the type of training programme, is manipulated.
  • 17. Experimental and control groups Experimental and control groups  An experimental hypothesis-testing research when a group is exposed to usual conditions, it is termed a ‘control group’, but when the group is exposed to some novel or special condition, it is termed an ‘experimental group’. Treatments  The different conditions under which experimental and control groups are put are  usually referred to as ‘treatments'. The two treatments are the usual studies programme and the special studies programme For example, if we want to determine through an experiment the comparative impact of three varieties of fertilizers on the yield of wheat, in that case the three varieties of fertilizers will be treated as three treatments.
  • 18. Experiment  Experiment: Experiment is a study in which a treatment, procedure, or program is intentionally introduced and a result or outcome is observed. For example, we can conduct an experiment to examine the usefulness of a certain newly developed drug. Experiments can be of two types viz., absolute experiment and comparative experiment. If we want to determine the impact of a fertilizer on the yield of a crop, it is a case of absolute experiment; but if we want to determine the impact of one fertilizer as compared to the impact of some other fertilizer, our experiment then will be termed as a comparative experiment. Often, we undertake comparative experiments when we talk of designs of experiments
  • 19.  Experimental unit(s): The pre-determined plots or the blocks, where different treatments are used, are known as experimental units. Such experimental units must be selected (defined) very carefully.
  • 20. Different Research Design  The research design can be classified based on study of research. Research design in case of exploratory research studies Research design in case of descriptive and diagnostic research studies Research design in case of hypothesis-testing research studies.
  • 21. Research design in case of exploratory research studies  Exploratory research is conducted to provide a better understanding of a situation.  It isn’t designed to come up with final answers or decisions. Through exploratory research, researchers hope to produce hypotheses about what is going on in a situation.  For example, if some crime happened, what is the first step police do? ( to search for clues that can help establish what has happened) i.e exploratory research  For example, if sales for a particular line of vehicles dropped during the latest quarter, as a researcher you might use exploratory research to provide insights about what caused the decrease in revenue
  • 22.  Suppose that you conducted interviews with potential car buyers and noticed that they seemed to be more excited about the new styles of other car brands than they were about the brand in question.  This might lead to the hypothesis that style preferences had changed, resulting in lower sales. You can’t really confirm or reject the hypothesis with exploratory research, though.  it’s helps to define the problem.  It is very flexible with regards to methods used for gaining insights and to develop hypothesis.
  • 23.  Literature search: A search of popular press (newspapers, magazines, etc.), trade literature, academic literature, or published statistics from research firms or governmental agencies for data or insight into the problem at hand.  Depth interviews : Interviews with people knowledgeable about the general subject being investigated.  Focus group: An interview conducted among a small number of individuals simultaneously; the interview relies more on group discussion than on directed questions to generate data.  case analysis : Intensive study of selected examples of the phenomenon of interest.
  • 24. Descriptive Research Design  We use descriptive research for following purpose: To describe the characteristics of certain groups. To determine the proportion of people who behave in a certain way. To make specific predictions. To determine relationships between variables
  • 25.  Cross sectional study: Investigation involving a sample of elements selected from the population of interest that are measured at a single point in time.  Longitudinal study: Investigation involving a fixed sample of elements that is measured repeatedly through time.  Continuous panel : A fixed sample of respondents who are measured repeatedly over time with respect to the same variables.  Discontinuous panel: A fixed sample of respondents who are measured repeatedly over time, but on variables that change from measurement to measurement.  Sample survey: Cross-sectional study in which the sample is selected to be representative of the target population and in which the emphasis is on the generation of summary statistics such as averages and percentages.
  • 26. hypothesis-testing research studies  Hypothesis-testing research studies are known as experimental studies  tests the hypotheses of causal relationships between variables.  It will permit drawing inference about causality.  Usually experiments meet this requirement  Three basic principles of experimental designs (1) the Principle of Replication; (2) the Principle of Randomization; (3) Principle of Local Control.
  • 27. Principle of Replication  The Principle of Replication: the experiment should be repeated more than once  The statistical accuracy of the experiments is increased.  Suppose we are to examine the effect of two varieties of rice. For this purpose we may divide the field into two parts and grow one variety in one part and the other variety in the other part. We can then compare the yield of the two parts and draw conclusion on that basis. But if we are to apply the principle of replication to this experiment, then we first divide the field into several parts, grow one variety in half of these parts and the other variety in the remaining parts. We can then collect the data of yield of the two varieties and draw conclusion by comparing the same.
  • 28. Principle of Randomization  The Principle of Randomization provides protection, when we conduct an experiment, against the effect of extraneous factors by randomization. For instance, if we grow one variety of rice, say, in the first half of the parts of a field and the other variety is grown in the other half, then it is just possible that the soil fertility may be different in the first half in comparison to the other half. If this is so, our results would not be realistic. In such a situation, we may assign the variety of rice to be grown in different parts of the field on the basis of some random sampling technique i.e., we may apply randomization principle and protect ourselves against the effects of the extraneous factors.  The principle of randomization, have a better estimate of the experimental error.
  • 29. Principle of Local Control  Principle of Local Control: Under it the extraneous factor, the known source of variability, is made to vary deliberately over as wide a range as necessary and this needs to be done in such a way that the variability it causes can be measured and hence eliminated from the experimental error. we first divide the field into several homogeneous parts, known as blocks, and then each such block is divided into parts equal to the number of treatments. Then the treatments are randomly assigned to these parts of a block. Dividing the field into several homogenous parts is known as ‘blocking’. In general, blocks are the levels at which we hold an extraneous factor fixed, so that we can measure its contribution to the total variability of the data