**Psy 242**

**Hypothesis Testing:
Comparing 2 means with t-tests in SPSS**

In this lab session, you will practice the steps for comparing two means in SPSS using t-tests. You will also learn how to import a text file for use as data in SPSS, and how to check for outliers in the data before testing your hypothesis.

The data file you will use for this lab is 242-lab-data-ttest.sav. This file contains data from an experiment on Spatial Cuing from Coglab. The hypothesis you will test is that reaction times to detect a light are faster when a valid cue is given for the location where the light will appear than when an invalid (misleading) cue is given for the location. (For more information on the experiment, see http://coglab.wadsworth.com/experiments/SpatialCueing/index.html.) Begin by right-clicking on the link to the data file in the preceding sentence, and saving the file on your hard drive. Then double-click the file you saved to start SPSS and open the file.

**1. Look for
outliers**

Before doing hypothesis testing, you should always do some *exploratory
data analysis* to check for errors and outliers. Because the mean is sensitive to outliers, one absurdly slow
reaction time could completely change the results of an experiment like this
one.

To check for outliers in SPSS, make the following selections on the menus:

**Analyze
-> Descriptive Statistics -> Explore**

Move the labels for
both columns that contain the dependent variable data (the columns *valid*
and *invalid* in this case) into the box labeled *Dependent List.* Then click OK.

Look at the stem-and-leaf plots and the box plots to see if SPSS identified any outliers. If so, remove them before doing further analyses. One way to remove outliers is to just delete the individual data points that are outliers by hand. Another is to use a filter in SPSS to exclude them. Here is how:

- Look at the exploratory data analysis and determine a value for each condition that will exclude the outliers but not exclude any non-outlying data points.
- Bring the SPSS data window back to the foreground (click on its icon on the taskbar)
- In the
menu select
**Data -> Select Cases** - Click on a condition that has outliers you wish to exclude
- In the
*Select*box, click the*If Condition is Satisfied*button - Click
the
*If*box just below that button - Type
the rule that will exclude the outliers into the box in the upper right of
the screen. For example, if you
are excluding times greater than 600 milliseconds from the variable
*Valid*you should type in:**valid <= 600** - Click
*Continue*, then click*OK*

**2. Follow steps
in the previous hypothesis testing handout or lecture notes for doing a t-test.**

**Name ______________________ Date _________________ Psy 242 Lab 1**

** **

**3. In complete
sentences, report the results below. ** Be sure to identify the data that you will analyze, state how many
data points were excluded as outliers and what criteria you used to exclude
them, restate the hypothesis that you were testing, state whether the results
confirmed the hypothesis or not, state the means and standard deviations of
each condition, and correctly state the results of the t-test. Turn in this page to receive credit for this
lab.

Here is an example of how a t-test could be reported (for a different experiment):

Mean exam scores were analyzed in
an independent samples *t*-test in which *testing condition* was the
independent variable. Three outliers
(defined as scores of less than 20%, identified as outliers by an SPSS stem and
leaf plot) were excluded from analysis.
I had predicted higher scores in the *caffeine *testing condition
than in the *no caffeine* condition.
This prediction was not confirmed.
The mean exam score with caffeine was 87% (*SD* = 2.3%), which was
not significantly greater than the mean exam score of 80% (*SD = 3.4%) * without caffeine, *t* (67) = 1.34, n. s.

**4. Re-do the
analysis without excluding outliers. **Remove
the filter (**Data -> Select Cases**;
select *All Cases*). Now
re-do the *t*-test without excluding any outliers. Report the results of this analysis as you
did for #3.

**5. From this
exercise, what would you conclude about the effects of outliers?**