Application: Two-Sample T-Tests

Application: Two-Sample t-Tests

The one-sample t-test discussed in Chapter 8 requires that you know the population mean. It is unusual to have this information, so most studies compare two samples. Each sample measures a different condition of the independent variable. For example before conducting a study, it is important to know if you would need to conduct a related-samples t-test or an independent-samples t-test. Independent samples are groups that are not related to each other. One group has been randomly selected without worrying about who is in the other group. Related samples are groups that are deliberately selected to be similar to each other. For example, you might want to select two groups that have similar heights. If height could affect the experiment, it's best to match the groups on that variable.

Note: As you move forward through the course, you will begin to see terms that you learned in previous chapters. For example, each time you practice, you should know how to state a hypothesis and be able to identify your independent and dependent variables. Each assignment will contribute to your depth of knowledge so that you can understand more and more about conducting research studies.

To prepare for this assignment:

Carefully review Chapter 9 in your text.

Review the PowerPoint for Chapter 9.

Consider the following study and data set:

Martha believes that a relaxation technique involving visualization will help people with mild insomnia fall asleep faster. She randomly selects a sample of 20 participants from a group of mild insomnia patients and randomly assigns 10 to receive visualization therapy. The other 10 participants receive no treatment. Each participant is then measured to see how long (in minutes) it takes him or her to fall asleep. Martha's data are below. The numbers represent the number of minutes each participant took to fall asleep.

No Treatment (X1) Treatment (X2)

22 19

18 17

27 24

20 21

23 27

26 21

27