Research Design in Hypothesis-Testing Research Studies

In hypothesis-testing research studies, also known as experimental studies, the researcher generally tests the hypotheses of causal relationships among variables. Besides, such type of studies needs those kinds of procedures, which will not only reduce the bias and increase reliability, but will also approve the drawing inferences about causality. Hence, when we discuss about the research design in such studies, we usually mean the experimental designs.

Experimental designs were discovered and developed by Professor R. A. Fisher, who was working at the Rothamsted Experimental Station, at the Centre for Agricultural Research in England. In fact, the study of experimental designs originated in agricultural research. Professor Fisher divided the agricultural fields/plots into different blocks and conducted experiments in each of them. Consequently, whatever information was collected from this, he found them to be very reliable. In this way, he was inspired to develop certain experimental designs to test the hypotheses about scientific investigations. In recent time, the experimental designs are being used in researches related to phenomena of several disciplines. Besides, since experimental designs originated in the context of agricultural operations, we still use, although in a technical sense, several agricultural terms, such as, treatment, yield, plot, block, etc., in the experimental designs.

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Different Research Designs

Research Design in Descriptive and Diagnostic Research Studies

Descriptive research studies describe the characteristics of a person or a group whereas diagnostic research studies determine the frequency of occurrence of something or its association with something else. From the research design point of view, the design of such studies should be rigid and should focus on the following:

(a) Objective of the study (what the study is about and why is it being made?)

(b) Methods of data collection (what techniques of data collection will be adopted?)

(c) Sample selection (how much material will be needed?)

(d) Data collection (where the required data can be found and with what time frequency should the data be related?)

(e) Data processing and analysis

(f) Reporting the findings

Given below is the difference between research designs of exploratory and descriptive research studies:

Type of study

Research Design

Exploratory

Descriptive/Diagnostic

Overall design Flexible design Rigid design
  1. Sampling design
Non-probability sampling design Probability sampling design
  1. Statistical design
No pre-planned design for analysis Pre-planned design for analysis
iii. Observational design Unstructured instruments for data collection Structured or well thought out instruments for data collection
iv. Operational design No fixed decisions about the operational procedures Advanced decisions about operational procedures
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Different Research Designs

Research Design in Exploratory Research Studies

Exploratory research studies, also known as formulative research studies, are conducted when there are very few or no earlier studies for reference. In this type of research design, a vague problem is chosen, which is followed by an exploratory research to find a new hypothesis. It lays emphasis on discovery of ideas and possible insights that help in identifying areas for future experimentation.

Purpose

1) It provides information to form a more precise problem definition or hypothesis.

2) It establishes research priorities.

3) It gives the researcher a feel of the problem situation and familiarizes him with the problem.

4) It collects information about possible problems in carrying out the research using specific collection tools and specific techniques for analysis.

In exploratory studies, the following three methods are generally used:

1) Survey of relevant literature

2) Survey of experienced individuals

3) Analysis of selected examples

Survey of Relevant Literature

Published literature are very good sources for the purpose of hypothesis generation and problem definition. Much of the published and unpublished data is available through books, journals, newspapers, periodicals, government publications, individual research projects, and data collected by the trade associations. Some of it could be relevant to the given problem situation. An analysis of existing literature may not provide the solution to the research problem, but, it surely gives a direction to the research process.

Survey of Experienced Individuals

Talking to individuals who have expertise and ideas about the research subject can be very useful for the study. Attempt should be made to gather all possible information about the subject of research from people who have specific knowledge about it. In this case, the experimenter must prepare a systematic interview schedule to collect information from the respondents. The success of this survey depends upon the freedom of response given to the respondent, expertise and communication skills of the respondents, and the conversational skills of the experimenter in extracting maximum information from the respondents.

Analysis of Selected Examples

This method involves the selection of examples, which reflect the problem situation. A thorough analysis of the examples is conducted. In certain cases, such type of study helps in identifying the possible relationships that exist between the variables. The relationships, their extent, and direction are then measured using conclusive research designs.

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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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Features of a Good Research Design

When a researcher has formulated a research problem, he/she has to focus on developing a good design for solving the problem. A good design is one that minimizes bias and maximizes the reliability of the data. It also yields maximum information, gives minimum experimental error, and provides different aspects of a single problem. A research design depends on the purpose and nature of the research problem. Thus, one single design cannot be used to solve all types of research problem, i.e., a particular design is suitable for a particular problem.

A research design usually consists of the following factors:

(i) The means of obtaining information;

(ii) The availability and skills of the researcher and his staff, if any;

(iii) The objective of the problem to be studied;

(iv) The nature of the problem; and

(v) The availability of time and money for the research work.

If a research study is an exploratory or formulative one, i.e., it focuses on discovery of ideas and insights, the research design should be flexible enough to consider different aspects of the study. Similarly, if the study focuses on accurate description or association between variables, the design should be accurate with minimum bias and maximum reliability. However, in practice, it is difficult to categorize a particular study into a particular group. A study can be categorized only on the basis of its primary function and accordingly, its design can be developed. Moreover, the above mentioned factors must be given due weightage while working on the details of the research design.

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