Steps to Follow When Conducting Research

The specific steps to follow when conducting research depend, in part, on the topic of investigation, where the researchers are in their overall program of research, and other factors. Nonetheless, much research in the social sciences follows a systematic course of action that begins with the statement of a research question and ends with the researcher drawing conclusions about a null hypothesis. This section describes the research process as a planned sequence that consists of the following six steps:

1.	developing a statement of the research question;
2.	developing a statement of the research hypotheses (i.e., specific questions to be tested);
3.	defining the instruments (e.g., questionnaires, unobtrusive observation measures);
4.	gathering the data;
5.	analyzing the data;
6.	drawing conclusions regarding the null and research hypotheses.

The preceding steps are illustrated here with reference to a fictitious research problem. Imagine that you have been hired by a large insurance company to find ways of improving the productivity of its insurance agents. Specifically, the company would like you to find ways to increase the amount of insurance policies sold by the average agent. You will therefore begin a program of research to identify the determinants of agent productivity.

The Research Question

The process of research often begins with an attempt to arrive at a clear statement of the research question (or questions). The research question is a statement of what you hope to learn by the time you have completed the study. It is good practice to revise and refine the research question several times to ensure that you are very explicit and precise.

For example, in the present case, you might begin with the question, “What is the difference between agents who sell a lot of insurance compared to those who sell very little insurance?” An alternative question might be, “What variables have a causal effect on the amount of insurance sold by agents?” Upon reflection, you might realize that the insurance company really only wants to know what things management can do to help agents to sell more. This might eliminate from consideration certain personality traits or demographic variables that are not under management’s control, and substantially narrow the focus of the research program. Upon further refinement, a more specific statement of the research question might be, “What variables under the control of management have a causal effect on the amount of insurance sold by agents?” Once you define the research question(s) clearly, you are in a better position to develop a good hypothesis that provides an answer to the question(s).

The Hypothesis

A hypothesis is a statement about the predicted relationships among observed events or factors. A good hypothesis in the present case might identify which specific variables will have a causal effect on the amount of insurance sold by agents. For example, a hypothesis might predict that agents’ level of training will have a positive effect on the amount of insurance sold. Or, it might predict that agents’ level of motivation will positively affect sales.

In developing the hypothesis, you might be influenced by any number of sources: an existing theory; some related research; or even personal experience. Let’s assume that you have been influenced by goal-setting theory that states, among other things, that higher levels of work performance are achieved when employees have difficult work-related goals. Drawing on goal-setting theory, you now state the following hypothesis: “The difficulty of goals that agents set for themselves is positively related to the amount of insurance they sell.”

Notice how this statement satisfies our definition for a hypothesis as it is a statement about the assumed causal relationship between two variables. The first variable can be labeled Goal Difficulty, and the second can be labeled Amount of Insurance Sold. This relationship is illustrated in Figure 1.1:

The same hypothesis could be restated in a number of other ways. For example, the following hypothesis makes the same basic prediction: “Agents who set difficult goals for themselves sell greater amounts of insurance than agents who do not set difficult goals.”

Notice that these hypotheses are stated in the present tense. It is also acceptable to state hypotheses in the past tense. For example, the preceding could have been stated: “Agents who set difficult goals for themselves sold greater amounts of insurance than agents who did not set difficult goals.” The verb tense of the hypothesis depends on whether the researcher will be examining data already collected or will undertake data collection at some future point.

You should also note that these two hypotheses are quite broad in nature. In many research situations, it is helpful to state hypotheses that are more specific in the predictions they make. A more specific hypothesis for the present study might be: “Agents who score above 60 on the Smith Goal Difficulty Scale will sell greater amounts of insurance than agents who score below 40 on the Smith Goal Difficulty Scale.”

Defining the Instrument, Gathering Data, Analyzing Data, and Drawing Conclusions

With the hypothesis stated, you can now test it by conducting a study in which you gather and analyze relevant data. Data can be defined as a collection of scores obtained when participants’ characteristics and/or performance are assessed. For instance, you might decide to test your hypothesis by conducting a simple correlational study. As an example, you might identify a group of 100 agents and determine:

• the difficulty of the goals that have been set for each agent;

• the amount of insurance sold by each agent.

Different types of instruments are used to obtain different types of data. For example, you can use a questionnaire to assess goal difficulty, but rely on company records for measures of insurance sold. Once the data are gathered, each agent will have a score indicating the difficulty of his or her goals and a second score indicating the amount of insurance that he or she has sold.

With the data in hand, you analyze these data to determine if the agents with the more difficult goals did, as hypothesized, sell more insurance. If yes, the study provides support for your hypothesis; if no, it fails to provide support. In either case, you draw conclusions regarding the tenability of your hypotheses. This information is then considered with respect to your research question. These findings might stimulate new questions and hypotheses for subsequent research and the cycle would repeat. For example, if you found support for your hypothesis with the current correlational study, you might choose to follow up with a study using a different method, such as an experimental study. (The difference between these methods is described later.) Over time, a body of research evidence would accumulate, and researchers would be able to review study findings to draw conclusions about the determinants of insurance sales.