Page 54 - Quantitative Data Analysis

Quantitative Data Analysis
Simply Explained Using SPSS

Potential Statistical Errors

In making a conclusion from our statistical analysis, there are four possible
conclusions that can be made:

1. Reject the null hypothesis that is false (correct conclusion).

2. Fail to reject a null hypothesis that is true (correct conclusion).

3. Reject a null hypothesis even though it is true (Type I Error).

4. Fail to reject a null hypothesis even though it is false (Type II Error).

Type I error – rejection of a null hypothesis when it is true.
Saying something is sig. when in fact it is not.

Type II error – failure to reject a null hypothesis that is false.
Saying something is not sig. when in fact it is

Type I and Type II errors
H o is true in H o is false in
population population
Researcher rejects H o Type I error Correct conclusion

Researcher does not reject Correct conclusion Type II error
H o

The probability of a Type I error is under the direct control of the
researcher when he/she sets the level.

The Theory and Applications of Statistical Inferences 38