Research Design: Important Concepts

In order to facilitate a clear and better understanding of the different research designs, it is initially necessary to define all the various important concepts of research design itself.

1) Dependent and independent variables: A variable is a concept that can take on different quantitative values. E.g., weight, height, income, etc. A dependent variable can be defined as the variable, which depends upon or is a consequence of the other variable. On the other hand, an independent variable can be defined as the variable that is antecedent to the dependent variable. E.g., if height depends upon age, then height is a dependent variable, while age is an independent variable.

1) Dependent and independent variables: A variable is a concept that can take on different quantitative values. E.g., weight, height, income, etc. A ‘dependent variable’ can be defined as the variable, which depends upon or is a consequence of the other variable. On the other hand, an ‘independent variable’ can be defined as the variable that is antecedent to the dependent variable. E.g., if height depends upon age, then height is a dependent variable, while age is an independent variable.

2) Extraneous variable: Although, the independent variables are unrelated to the study purpose, they might however affect the dependent variables, known as extraneous variables. E.g., When a researcher investigates the hypothesis of the relationship between children’s gains in moral studies achievement and their self-concepts. The self-concept denotes an independent variable, whereas the moral studies achievement denotes a dependent variable. However, intelligence may also affect the moral studies achievement, but as it is unrelated to the study purpose, it will thus be called an extraneous variable.

3) Control: The most significant quality of a good research design is to reduce the influence/effect of extraneous variables. Control is a technical term, which is used while designing the study, by reducing the effects of extraneous independent variables. Besides, in experimental studies, the term control refers to the restraining of experimental conditions.

4) Confounded relationship: In case the dependent variable is bound by the influence of extraneous variable, the relationship between the dependent and independent variables is known to be confused by extraneous variables.

5) Research hypothesis: This can be defined as the prediction or a hypothesised relationship that needs to be tested by scientific methods. Besides, it is a predictive statement, which connects an independent variable to a dependent variable. Moreover, a research hypothesis needs to contain, at least, one independent and one dependent variable.

6) Experimental and non-experimental hypothesis-testing research: When a research aims at investigating a research hypothesis, it is known as the hypothesis-testing research. However, it can be of the experimental or the non-experimental design. On the other hand, a research in which the independent variable is manipulated is known as the experimental hypothesis-testing research, while the research in which an independent variable is not manipulated is known as the non-experimental hypothesis-testing research.

7) Experimental and control groups: When any group is exposed to the usual conditions of an experimental hypothesis-testing research, it is known as a control group. Whereas, when the group is exposed to some other special condition, it is known as an experimental group.

8) Treatments: This can be defined as the different types of conditions under which the experimental and control groups are put. E.g., In order to determine the comparative impact of three varieties of fertilizers on a crop yield, the three different varieties of fertilizers will be treated as three different treatments.

9) Experiment: This can be defined as the process of examining the truth of a statistical hypothesis, relating to some research problem. E.g., An experiment conducted in order to research the usefulness of a newly developed medicine.

Moreover, experiments can be of two types:

i. Absolute experiment  The determination of the impact of a fertilizer on a crop yield is an example of absolute experiment.

ii. Comparative experiment  The determination of the impact of one fertilizer, in comparison to another fertilizer, is an example of comparative experiment.

10) Experimental units: These represent the pre-determined plots or blocks, where different types of treatments are used. Moreover, such type of experimental units must be selected, as well as defined, very cautiously and thoroughly.

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