# Variation F-test

To calculate if there is a significant difference between variation of the two data-sets. It calculates the F-test between this column and the comparing column. ### Interpretation

• The smaller the p value is the more likely there is a significant difference in the variation of the data-sets.
• Develve uses the commonly accepted value of p < 0.05 for significance.
• For a good power (0.8 in Develve) the sample size for both data sets must be bigger than the minimum sample size calculated.
• For a good F-test the data-sets must be normally distributed see Anderson Darling normality test.

### Colors of the cells

• Red
Data-set is not normally distributed
• Green
No significant difference
• Yellow
Significant difference
• Orange
Sample size to small

## Formula Calculating F value Where s1 is the smallest of the comparing STDEV values.

With the F value and the degrees of freedom can the program calculate the p value.

### Sample size

#### not equal This results in the degrees of freedom out of the table, the Minimum sample size is #### bigger smaller This results in the degrees of freedom out of the table, the Minimum sample size is ## Legend

n = n = STDEV smallest variation = STDEV biggest variation Degrees of freedom

## Example

Select Variation test. To use the F-test test first unselect "non normal distributed" when the box is selected the Levene test is calculated. Then select Diff variation.
• The difference in variance between data set A and B is not significant (Row F test p >0.05) and the sample size is to small (Row min Samples 240).
• The difference in variance between data set A and C is significant (Row F test p <0.05) and the sample size is big enough.
• The difference in variance between data set A and D is not significant (Row F test p >0.05) and the sample size is big enough. Data file