t-test

The t-test is to test if there is a significant difference in Mean of two data sets (2 sample t-test) or one data set and a specific value (one sample t-test).

1 sample t-test

If Diff mean is selected and one of the comparing column contains 1 value the 1 sample t-test is calculated. To calculate the if there is a significant difference in Mean between a dataset and a Hypothesized value.

Interpretation

The smaller the p value is the more likely there is a significant difference between the dataset and the hypothesized value.
In Develve for a significant difference the p value must be below 0.05.
For a good power (0.8 in Develve) the sample size data sets must be bigger than the minimum sample size calculated.
For a good t-test the datasets must be normally distributed see Anderson Darling normality test.

Options

Bigger/Smaller (one sided test) or not equal test (two sided)

Colors of the cells

Green No significant difference
Yellow Significant difference
Red Not normally distributed
Orange Sample size to small

Formula

With the t value and the degrees of freedom can the program interpolate the p value out of the t table.

Sample size

The result is the minimum sample size of the dataset.

not equal

bigger smaller

Example 1 sample t-test (not equal)

To use the 1 sample t-test test first unselect "non normal distributed" when the box is selected the 1 sample Wilcoxon median test is calculated.. Then select Diff mean.

0 is significant not equal with the dataset A and the sample size is big enough (Row t-test p <0.05).

2 sample t-test

If Diff mean is selected the 2 sample t-test is calculated between this column, and the comparing column if this column and the comparing column contains more than 1 value. To calculate if there is a significant difference in Mean between the two datasets.

Interpretation

The smaller the p value is the more likely there is a significant difference between the 2 datasets.
In Develve for a significant difference the p value must be below 0.05.
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 t-test the datasets must be normally distributed see Anderson Darling normality test.

Options

Bigger/Smaller (one sided test) or not equal test (two sided)

Colors of the cells

Green No significant difference
Yellow Significant difference
Red Not normally distributed
Orange Sample size to small

Formula Calculating t value

Formula Calculating the amount of degrees of freedom

With the t value and the degrees of freedom can the program interpolate the p value out of the t table.

Sample size

is the biggest one of the two comparing data sets. The result is the minimum sample size for both data sets.

not equal

bigger smaller

Example 2 sample t-test (not equal)

To use the 2 sample t-test test first unselect "non normal distributed" when the box is selected the 2 sample Mann-Whitney median test is calculated. Then select Diff mean.

The difference between data set A and B is not significant and the sample size is to small (Row t-test p >0.05).
The difference between data set A and C is significant and the sample size is big enough (Row t-test p <0.05).
The difference between data set A and D is not significant and the sample size is big enough (Row t-test p >0.05).

Paired t test

The paired t test is a modified version of the 1 sample t test. To conduct a Paired t-test subtract the two comparing data stets and run a 1 sample t test on this resulting data set. By comparing this data set with a column with as only input 0.