Topic 8 Paired Sample T-Test
Before, with the independent sample t-test, we wanted to test if the population mean of a group was equal to the population mean of another (independent) group.
Now, we want to do a similar analysis where groups are no longer independent. We want to compare the the means of a variable for the same individuals, at different times periods.
This is called the Paired Sample T-Test
We will use this test to examine the means of one continuous across different time periods.
8.1 Formulas and calculations
Steps:
- Calculate the difference between pre and post values, call it d
- Calculate the mean of this difference
- Calculate the standard deviation of this difference
- Use the standard deviation to calculate the standard error.
- Use the mean and standard deviation in the Paired Sample T-Test formula.
Calculations:
- is simply: d=post−pre
To perform (2) and (3), you need to use the following table:
d | f | fd | d−¯d | (d−¯d)2 | f(d−¯d)2 |
---|---|---|---|---|---|
… | … | … | … | … | … |
. | ∑f | ∑fd | ∑=SSd |
- Calculate the mean of this difference
¯d=∑fd∑f
- Calculate the standard deviation of this difference
sd=√∑SSdn−1
Use the standard deviation to calculate the standard error. se=sd√n
Use the mean and standard deviation in the Paired Sample T-Test formula.
tpaired=¯dse
8.2 Interpretation
Compare your calculated t to the tcritical from the t-table.
- if the calculated t is higher than the critical value (tcritical), we reject the null hypothesis.
- if the calculated t is lower than the critical value (tcritical), we do not reject the null hypothesis.
8.3 Interpretation of SPSS results
Once again, we look at the p-value:
- p≤α we reject the null
- p>α we fail to reject the null
8.4 Exercise
First, I will illustrate with the sample test scores dataset.
Second, using the “school-data.sav” do the necessary procedures to check if the there was an increase in api scores between 1999 and 2000 in the schools in the sample.
- What is your null hypothesis?
- What is the alternative hypothesis?
- What is your alpha?
- Interpret your p-value.