What if in the real world no relationship exists between the variables, but the test found that there was a significant relationship? In this case, you would be making a false positive error because you falsely concluded a positive result (you thought it does occur when in fact it does not).
On the other hand, what if in the real world a relationship does exist between the variables, but the test found that there was no significant relationship? In this case, you would be making a false negative error, because you falsely concluded a negative result (you thought it does not occur when in fact it does).
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. |