Compute Independent Samples
Prepare your Datafile to Compute Independent Samples
Let’s see the steps for calculating an independent-samples t-test.
Recall from Week 5 that data must be configured differently for between-subject designs. You will need to open a new worksheet (click on the + at the bottom of the page) and copy your data for the dependent variable over.
In the new worksheet divide your data into two columns to agree with the two levels of your independent variable.
Let’s look at an example, where we hypothesize that there will be significant differences between boys and girls on scores of anxiety. Here, sex is your independent variable with two levels, 1 (female) and 2 (male). Your dependent variable is RCMAS-Pretreatment.
4. Begin by first sorting your data by your independent variable so you have all individuals in each level grouped together.
a. Put your cursor on the title of the variable, Click Data, and then under sort, click the AZ option. Microsoft Excel will sort all data on your spreadsheet so that values of all other variables remain with the original participant.
5. Open a new worksheet (click the plus sign) and in column A Type the name of your first level. In column B, type the name of your second level.
a. Copy the values on your dependent variable for each group into the appropriate column.
b. Right click on the worksheet tab and rename it to identify the analysis you are conducting.
Conduct an Independent-Samples t-Test
1. Click Data, click Data Analysis
2. Scroll down and select t-Test: Two-Sample Assuming Equal Variances
3. Click OK
4. Complete the information in the pop-up box.
a. Put your cursor in the box for Variable 1 Range and select the data for one level of your independent variable, including the label.
b. Put your cursor in the box for Variable 2 Range and select the data for the second level of your independent variable, including the label.
c. Check the box for Labels
d. Make certain your Alpha is set to 0.05
e. Select the radio button for Output range and select an area of your worksheet to the side of your data.
f. Click OK
g. Change the name of your worksheet to two-sample t-test
5. Reformat your data to the appropriate font and number format (change general to number)
You will see the output in the following format:
These data give you the mean, the variance, and the number of participants (observations) for each group. Note you will need to compute the SD, which is the square root of the variance. This is followed by the pooled variance, hypothesized mean difference (null hypothesis), and df (needed for your APA-formatted formal report). Following df is the information that will enable you to interpret this test. You are interested in the absolute value of the t-statistic and the p-value for the one-tail and the two-tail tests along with the critical value.
Here we conducted a two-tailed test (hypothesizing a difference, but not the direction that difference would take). Our t = |1.02|, with p = 0.33 and a critical value of 2.23 for a two-tailed test. Because t of |1.02| is less than the critical value, we can see there is no difference between the two means. This is confirmed by the p-value of 0.33, which is greater than the needed 0.05 for significant differences. For these data, your p-value is greater than .05; so, you will not reject the null. Although it appears as if there is a difference between the two means, your p-value of 0.33 tells you that if you were to reject the null, you have a 33% probability of having a Type 1 error, which is unacceptable. These results may have been obtained by chance alone.
In your report, the data would be written in APA format as follows:
Results
An independent-samples t-test was run to test the hypothesis that there are differences in anxiety between boys and girls. The test was not significant
(t(10) = -1.02, p = 0.33). Boys (M = 21 SD = 2.76) do not differ from girls (M = 23, SD = 3.95) in their levels of anxiety.
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