Integrity Post Processing
Check the integrity of data.
Check Integrity of Data
Review a series of statistical measures on input variables and output responses in the Integrity post processing tab.
 From the Post Processing step, click the Integrity tab.

From the Channel selector, select a category of information to display in the
table.
 Health High level summary of statistics used to easily spot inconsistent, nonchanging, or missing data.
 Summary Basic descriptive statistics that presents information on the data in groups such as quartiles or ranges.
 Distribution Detailed descriptive statistics used to quantitatively describe the distribution of data points.
 Quality Values typically used in Quality Engineering.
Integrity Tab Data
Each column in the Integrity tab displays a statistical indicator for output responses.
 Column
 Description
 Avg Dev (Average Deviation)
 Average deviation is evaluated using:$$\frac{{\displaystyle \sum _{i=1}^{{\rm N}}\left{x}_{i}\overline{x}\right}}{{\rm N}}$$In Figure 2, the horizontal line represents the average of the values in the vector. The vertical lines represent the differences between the values of the vector and the average of the values. The average deviation is the average difference between the vector elements and the average of the vector elements. The sign of each element is not taken into consideration when calculating the deviation. The sign of each element is taken into consideration when calculating the average of the elements.
 CoV (Coefficient of Variation)
 Measure of the relative dispersion given by:$$CoV=\frac{S\mathrm{tan}dard\text{}Deviation}{Mean}$$
 Kurtosis
 Measure of the flatness of a distribution.
 LCL (Lower Control Limit)
 Mean  3*standard_deviation
 Maximum
 The largest of all output response values.
 Mean
 The most probable value the output response would take.
 Median
 The median of a scalar is that value itself.
 Minimum
 The smallest of all output response values.
 Outliers
 Outliers are data points that fall outside the whiskers of a box plot. To learn more about outliers, refer to About Box Plots.
 RMS
 The square root of the mean of the sum of the squares of all output
response values is calculated using:$$\sqrt{\frac{{\displaystyle \sum {x}_{i}^{2}}}{{\rm N}}}$$
 Skewness
 Indicates whether the probability distribution is skewed to the right or to the left. If the skewness is zero, the probability distribution is symmetric about the mean of the distribution. If the skewness is less than zero, the probability distribution is skewed to the left of the mean of the distribution. If the skewness is greater than zero, the probability distribution is skewed to the right of the mean of the distribution.
 Standard Deviation
 Square root of the variance.
 UCL (Upper Control Limit)
 Mean + 3*standard_deviation
 Variance
 Evaluated using:$$\frac{{\displaystyle \sum _{i=1}^{{\rm N}}{\left({x}_{i}\overline{x}\right)}^{2}}}{{\rm N}1}$$