Basic Research Concepts: A Handy Reference

Applied research—Using basic research methods, the outcome of the research is applied to a business problem.

Basic research—The clinical or scientific method of research. This type of research is often done in laboratories or under controlled circumstances.

Four Types of Research Methods: Reporting—A summary or incomplete review of existing data; Descriptive—Most often used in marketing or sales. This type of research always asks who, what, when, where, why, and how in research questions; Exploratory—Using focus groups or a small study to get a feel for the problem; Predictive/Causal—Research conducted where one unit is held steady, while the experiment is conducted on the other unit, which tests whether the experiment itself is the reason for change in the experimental unit.

Time Factors for Research: Longitudinal—A research study performed on a sample over a period of time; Cross-sectional—A research study done only once, which provides a snapshot of what is occurring somewhere at a particular time.

Four Types of Research Validity: Construct Validity—the theoretical or practical underpinnings of the hypotheses and measurement of the variables; External Validity—the comparability or generalizability of the findings to other samples and settings; Internal Validity—for descriptive, explanatory, or causal studies this is basically an answer to the question of whether we saw what we thought we saw; Conclusion Validity—did we use the proper statistical tools to draw these conclusions?

Operational definition—is a definition stated in terms of specific testing or measurement criteria. These terms must have empirical referents, which means we must be able to count or measure them in some way. The object to be defined can be physical one (i.e., a machine tool), or it can be abstract one (i.e., achievement motivation).

Level of Measurement—the characteristic of the data with respect to alphabetic and numerical values assigned to represent it, such as the measures of variables on surveys. Data can be represented at four levels of measurement:

• Nominal—e.g., Male/Female; The word nominal means in name only. Nominal variables are used on surveys to describe or identify the population being sampled;
• Ordinal—e.g., Rare, Medium Rare, Medium, Medium Well, Well Done; An ordinal measure can capture how a person feels on an issue, which is the case when the distance between each of the measure cannot be determined scientifically;
• Interval—e.g., Temperature or 1 to 5 satisfaction scales; with Interval measures, the distance between each unit of measure has a precise distance. For example, how long does it take ten trucks on the loading dock to unload a full container of merchandise?
• Ratio—Age in years, relative time, relative distance or relative temperature. Ratio data is captured with absolute measures; height, weight, distance, and money are all examples of ratio data.

Unit of Analysis—a classification of the individual, group, company, or societal unit under study. It is relevant because comparison of data from different units of analysis is frequently used to draw conclusions that while they seem logical are, in fact, erroneous.

For example, predicting the outcome of local elections based on a national survey or predicting the outcome of national elections based on a local survey. This fallacy involving misapplication of the unit of analysis is related to the ecological and exception fallacies. Consider this important issue in research, especially when using secondary data (i.e., data collected by somebody else for a different research question), as it is not always clear whether one is examining the individual, group, company, industry, etc.

For example, news commentators sometimes compare mismatched units of analysis and draw conclusions that may not be correct. If one draws conclusions about a group from one individual case, that is the exception fallacy. If one draws conclusions about an individual because they are part of group, that is an ecological fallacy.

For example, you know of several people who are Razorback fans and observe that they each own a red pickup truck. If you then meet a Razorback fan at the university, can you assume that they own a red pickup? No, because of the potential for ecological fallacy; you've erroneously assigned a group attribute to an individual. If you then meet red pickup trucks on the road, should you yell “Soooeee...” out the window at each one of them? No, because of the exception fallacy; it is possible that you have assigned an individual attribute to the entire group. The problem in both cases is that the unit of analysis of the information under examination does not match the type of research question at hand. Hence, there is a possibility of committing a unit of analysis fallacy.