Designing a Research Project
All science advances through the rigorous application of the scientific method. Part of this process involves the development of an empirical research design that can help researchers determine whether or not the hypothesis being tested is likely to be true. Good research design is based on a researcher's empirical observations and a review of the scientific literature. The information garnered from these sources is then formulated into a testable hypothesis that can be analyzed using inferential statistics. The research design used to test this hypothesis needs to not only consider the effect of various levels of the independent variables on the dependent variables, but also control as much as possible any extraneous variables that are not related to the research question but which might affect the results. The experimental data are analyzed to determine their statistical significance and the likelihood the null hypothesis is true using statistical tests.
Progress in the physical, behavioral, and social sciences is made through the systematic and rigorous application of the scientific method to observed real-world phenomena. The scientific method comprises the general procedures, guidelines, assumptions, and attitudes required for the organized and systematic collection, analysis, interpretation, and verification of data that can then be reproduced. The goal of the scientific method is to articulate or modify the laws and principles of a science. As shown in Figure 1, steps in the scientific method include
* problem definition based on observation and review of the literature;
* formulation of a testable hypothesis;
* selection of a research design;
* data collection and analysis;
* extrapolation of conclusions; and
* development of ideas for further research.
Observing & Researching Phenomena
Typically, scientific research begins with the scientist's empirical observations. For example, I might observe that when I wear a business suit to a meeting even when other people are wearing more casual clothes, I tend to be afforded more respect than when I wear less formal attire. If curious, I might next look at social science literature to see if anyone else has observed such incidents and hypothesized an underlying cause. I might find that there is a large body of research on how to "dress for success." My literature review might reveal that other scientists have not only observed these behaviors but also theorized about their causes and conducted research to test their theories. Problem definition relies on both of these sources of information: the researcher's observations of real-world phenomena and the research results and theories that are described in the scientific literature.
If the literature review has not answered all my questions and I am still curious about the nature of this phenomenon, my next step would be to formulate a testable hypothesis. This is not necessarily as easy as it sounds; although it might be relatively easy to articulate a naïve theory concerning the relationship between attire and success in the workplace, such as that people who wear business attire are more likely to be successful at work, such statements are vague and not testable. To be able to test this tentative hypothesis using the scientific method, one must determine what factors are important in this theory and then operationally define the associated terms.
Identifying & Defining Variables
In the simplest research design, a stimulus, such as a person wearing either business attire or casual attire, is presented to the research subjects--in this case, potential customers, supervisors, or other people who might be encountered in a business setting. The responses of the subjects are then observed and recorded. From a research design point of view, both the stimulus and the response are called variables. The variables of most concern in the design of a research study are the independent variable, which is the stimulus or experimental condition that is hypothesized to affect the outcome (e.g., how one dresses in the workplace), and the dependent variable, which is the observed effect on outcome caused by the independent variable (e.g., the reactions of research subjects to people wearing business attire). As shown in Figure 2, researchers must also consider extraneous variables, or variables that can affect the outcome of the experiment but have nothing to do with the independent variable itself. For example, if the person wearing either business or casual attire is rude when interacting with a research subject, this rudeness will probably have a much stronger effect on the subject's response than how the person is dressed. Similarly, if the person has visible tattoos, is poorly groomed, or looks like the subject's ex-spouse, the subject's response may be a reaction to these extraneous variables rather than to the independent variable. Any number of extraneous variables may affect an experiment. The more of these variables that are accounted for and controlled in the experimental design, the more meaningful the results of the research study will be.
In addition to determining which variables are important in the research study, it is also essential to operationally define them. An operational definition is a definition that is stated in terms that can be observed and measured. In this example, the researcher might operationally define "business attire" as a dark suit with a white shirt or blouse. "Casual attire" might be operationally defined as shorts and a t-shirt. However, by operationally defining these terms in this manner, the researcher is by necessity limiting the generalizability of the research results. With these definitions, the researcher will only be able to draw a conclusion about subjects' reactions to people wearing dark suits and white shirts or blouses versus their reactions to people wearing shorts and t-shirts. A whole range of other work-appropriate attire exists: sports coats and blazers, colored shirts or blouses, Bermuda shorts, polo shirts, and any other type of clothing that could be worn in the workplace. The researcher must decide how many of these options are important to the theory and should be tested in the experiment. The researcher, believing that it is important to look at a range of clothing options, might decide that several conditions of the independent variable are needed--formal business attire, informal business attire, and business casual clothing, for example--and design an experiment that examines subjects' reactions to all three levels of formality. Or, based on the research literature, the experimenter might conclude that formal business attire has already been demonstrated to result in better treatment in the workplace and decide to examine the limits of this conclusion. Accordingly, he or she might design an experiment in which subjects are exposed to people variously wearing black suits, charcoal gray suits, and navy suits with white shirts or blouses to see if there is any difference in the way that the subjects react. At some point, however, the researcher will have to limit the definitions of the variables to a manageable number, which is done in part by determining which inferential statistical techniques are available to analyze the data.
Constructing a Hypothesis
After the variables are identified and defined, the researcher will develop a formal hypothesis for the experiment that can be analyzed with...
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