Mean

n

Median

STDEV

Cp Cpk % out of tolerance

Min/Max

Compare with

Calculate Difference

Diff mean normally

Diff median not normally

Diff variation normally

Diff variation not normally

Normally test

Correlation

Regression

Kurtosis

Skewness

For commersial use

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The t-test tests if there is a significant difference in Mean between two data sets (2 sample t-test) or one data set and a specific value (one sample t-test). The t-test also called "student's t-test" and follows the t distribution. This distribution is based on the normal distribution and whit a high sample size the shape is the same.

- The smaller the p value is the more likely there is a significant difference between the data-set and the hypothesized value.
- Develve uses the commonly accepted value of p < 0.05 for significance.
- 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 data-sets must be normally distributed see Anderson Darling normality test.
- If the data set is not normally distributed see "What to do with not normally distributed data". The 1 sample Wilcoxon median test is the non parametric counter part of the 1 sample t-test.

- RedData-set is not normally distributed
- GreenNo significant difference
- YellowSignificant difference
- OrangeSample size to small

With the t value and the degrees of freedom the program calculate p value.

- E is significant not equal with the data-set A and the sample size is big enough (Row
*t-test p*<0.05).

Data file

- The smaller the p value is the more likely there is a significant difference between the 2 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 t-test the data-sets must be normally distributed see Anderson Darling normality test.
- If the data set is not normally distributed see "What to do with not normally distributed data". The 2 sample Mann–Whitney-test is the non parametric counter part of the 1 sample t-test.

- RedData-set is not normally distributed
- GreenNo significant difference
- YellowSignificant difference
- OrangeSample size to small

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

- 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).

Data file

Then compare the column C with the comparing value in this case 0.

Data file

In this example the difference between A and B is not significant difference with 0 and the sample size is to small for this difference.

s = STDEV

= Mean

= Hypothesized value

= Mean difference between to data sets

- http://en.wikipedia.org/wiki/T-test
- http://www.itl.nist.gov/div898/handbook/prc/section2/prc22.htm
- http://www.itl.nist.gov/div898/handbook/eda/section3/eda353.htm
- http://www.socialresearchmethods.net/kb/stat_t.php