SPSS Statistics For Dummies, 4th Edition
Book image
Explore Book Buy On Amazon
When conducting a statistical test, too often people jump to the conclusion that a finding “is statistically significant” or “is not statistically significant.” Although that is literally true, it doesn't imply that only two conclusions can be drawn about a finding.

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.

About This Article

This article is from the book:

About the book authors:

Jesus Salcedo is an independent statistical and data-mining consultant who has been using SPSS products for more than 25 years. He has written numerous SPSS courses and trained thousands of users. Keith McCormick has been all over the world training and consulting in all things SPSS, statistics, and data mining. He now authors courses on the LinkedIn Learning platform and coaches executives on how to effectively manage their analytics teams.

This article can be found in the category: