Interpreting Statistical Significance in SPSS Statistics

By Keith McCormick, Jesus Salcedo, Aaron Poh

Part of SPSS Statistics For Dummies Cheat Sheet

You need to know how to interpret the statistical significance when working with SPSS Statistics. When conducting a statistical test, too often people immediately jump to the conclusion that a finding “is statistically significant” or “is not statistically significant.” While that is literally true, it does not imply that there are only two conclusions to draw about a finding.

What if in the real world there is no relationship between the variables, and the test found that there was a significant relationship? In this case, you would be making an error; this type of error is called a “false positive” because you falsely conclude a positive result (think it does occur).

On the other hand, what if in the real world there is a relationship between the variables, and the test found that there was no significant relationship? In this case, you would be making an error; this type of error is called a “false negative” because you falsely conclude a negative result (think it does not occur).

In the Real World Statistical Test Results
Not Significant (p > 0.5) Significant (p < 0.5)
The two groups are not different The null hypothesis appears true, so you conclude the groups
are not significantly different.
False positive.
The two groups are different False negative. The null hypothesis appears false, so you conclude that the
groups are significantly different.