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

75 EURO

If Correlation test is selected and and the comparing column contains 4 or more values in the same row the regression formula is calculated.

Calculates the linear regression formula between two comparing columns.

The correlation does

- The resulting formula is the fitted line between the two data sets. With this formula you can calculate the Y value out of a given X value.
- For a good regression calculation there must be an Correlation between the data sets.

y = Comparing column

Data file

Proportions

Chi Square test

One way Anova

Kruskal-Wallis Test

Variation Levene test

Multiple Correlation

Multiple linear Regression

Generate Distribution

Calculations

Filter

Box-Cox transformation

Gauge R&R

Distribution fitting

Graphs

For commersial use

75 EURO

- The resulting formula is the fitted line between the two or more data sets. With this formula you can calculate the Y value out of a given X value.
- The p value of the T-test of the predictor indicates if a predictor is significant
- The P value of the Anova is an indication if there is at least one significant predictor.
- RÂ²adj indicates how good the data is fitting the regression model the higher the value the more significant.
- For a good regression calculation the residual must be normally distributed Normally p higher than 0.10.

The formula is put in to matrices.

To Calculate the factors the following formula is used

To calculate the correlation coefficient the following formulas are used.

df | SS | MS | |

Total | n-1 | ||

Regression | k | ||

Error | n-k-1 |

= inverse matrix

= y value predicted by the formula

= Average y value

= error

= multiple correlation coefficient

According the Anova there is at least one predictor significant. Looking to the T-test predictor A is significant. And the the normality of the residual is OK it is bigger than 0.10.

Data file

- http://en.wikipedia.org/wiki/Linear_regression
- http://en.wikipedia.org/wiki/Matrix_%28mathematics%29