One-sample t-tests compare an observed mean to a hypothesized value in a given population
For instance, let's say researchers believe that the majority of households in the United States have at least two televisions. They collect a representative sample from the general population and find that on average there are four televisions. This difference of two televisions between what they expected (M = two televisions per household) and what the actual value (M = four televisions per household) may be statistically significant when using a one-sample t-test.
The most important part of using a one-sample t-test is to state the hypothesis for the expected mean value in an a priori fashion.
The steps for conducting a one-sample t-test in SPSS
2. Click Analyze.
3. Drag the cursor over the Compare Means drop-down menu.
4. Click One Sample T Test.
5. Click on the continuous outcome variable to highlight it.
6. Click on the arrow button to move the variable into the Test Variable(s): box.
7. In the Test Value: box, enter the a priori hypothesized mean value that researchers expect to occur.
8. Click OK.
The steps for interpreting the SPSS output for a one-sample t-test
2. In the One-Sample Test table, look under the Sig. (2-tailed) column for the p-value that is interpreted.
If the p-value is LESS THAN .05, then the observed mean is significantly different than what researchers hypothesized or expected.
If the p-value is MORE THAN .05, then the observed mean is NOT significant different that what researchers hypothesized or expected.
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