Skip to main content Accessibility help
Internet Explorer 11 is being discontinued by Microsoft in August 2021. If you have difficulties viewing the site on Internet Explorer 11 we recommend using a different browser such as Microsoft Edge, Google Chrome, Apple Safari or Mozilla Firefox.
Home
> Looking for Differences Between…

Chapter 8: Looking for Differences Between Two Treatments

Chapter 8: Looking for Differences Between Two Treatments

pp. 177-202

Authors

, Ithaca College, New York, , Ball State University, Indiana
Resources available Unlock the full potential of this textbook with additional resources. There are Instructor restricted resources available for this textbook. Explore resources
  • Add bookmark
  • Cite
  • Share

Summary

CHAPTER PREVIEW

In the previous chapter we provided an overview of probability theory and statistical hypothesis testing. We can use statistical tests when we conduct experimental studies. Statistical tests are one part of applying experimental methods that allow researchers to establish a cause-andeffect relationship between an independent variable and a dependent variable. Experimental designs employ random assignment, which allows us to establish cause-and-effect relationships. Random assignment ensures that each person has an equal chance of ending up in a group on the basis of an objective placement. In the simplest experiment, the researcher compares a treated group (experimental) to a control (nontreated) group. This simple two-group design, or independent measures design, allows the researcher to compare two different levels of the independent variable using two different groups of people.

Instead of using two different groups, we can also design an experiment using only one group and ask participants to engage in both the treatment and control conditions of the study. In this case, we are still testing two levels of the independent variable, but we are using one group of people and asking them to participate in both conditions. The repeated measures design, using one group of people in both conditions, allows us to test the effect of the two levels of the independent variable using only one group of people. In each of these instances we are using two levels of a single independent variable, and we are measuring a single dependent variable. In the first case, we are using an independent samples design or a two-group design, and in the second instance we are using a related-samples or repeated measures design.

In many research studies, we use several different levels of the independent variable. For example, we might test the effect of three different amounts of caffeine. The simplest design employs only two levels of the independent variable. In this chapter, we will describe how to use inferential statistics to test differences between only two levels of the independent variable. The independent samples t test is used to test differences between two groups. The related samples or repeated measures t test is used to detect differences when one group of participants experiences both levels of treatment.

About the book

Access options

Review the options below to login to check your access.

Purchase options

eTextbook
US$79.99

Have an access code?

To redeem an access code, please log in with your personal login.

If you believe you should have access to this content, please contact your institutional librarian or consult our FAQ page for further information about accessing our content.

Also available to purchase from these educational ebook suppliers