While this can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control on how or what kind of data was collected.Īll of the above research methods are correlational designs. Some researchers conduct archival research by using existing records. While this allows for results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data, which is discussed later. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. These can be a series of simple questions, in-depth interviews, or well-controlled experiments.Įach of these research methods has unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. Other approaches involve interactions between the researcher and the individuals who are being studied. Some methods rely on observational techniques. There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Compare longitudinal and cross-sectional approaches to research.Discuss the strengths and weaknesses of case studies, naturalistic observation, surveys, and archival research.Describe the different research methods used by psychologists.We explain more about the dependent t-test on the next page.By the end of this section, you will be able to: It is important to note that the two related groups do not need to be normally distributed themselves – just the differences between the groups. You can do this by simply subtracting each individuals' score in one group from their score in the other related group and then testing for normality in the normal way (see our Testing for Normality guide to learn how to test for normality in SPSS Statistics). In addition, the distribution of the differences between the scores of the two related groups needs to be normally distributed. The types of variable needed for the dependent t-test have already been discussed earlier in this guide. What are the assumptions of the dependent t-test? Remember, however, that this is unlikely to be the preferred statistical analysis for this study design. You then measure the differences between the interventions at the end, and only at the end, of the two interventions. ![]() In order to assess this study using a dependent t-test, you would use the same participants for the control trial as the diet counselling trial. During this control trial, the participants could either receive "normal" counselling or do nothing at all, or something else you deem appropriate. However, to improve the study design you also include want to include a control trial. To study this you could simply measure participants' weight before and after the diet counselling course for any changes in weight using a dependent t-test. For example, you might want to investigate whether a course of diet counselling can help people lose weight. One example of this design is where you have one of the interventions act as a control. The most common, more complex study design where you might use the dependent t-test is where you have a crossover design with two different interventions that are both performed by the same participants. You can also use the dependent t-test to study more complex study designs although it is not normally recommended. How else might you use the dependent t-test?
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