Perform advanced engineering statistical analysis.

QESuite enables you to perform the analyses below using functions

Capability Analysis

• Capability Analysis

  Calculates the all four capability indices: Cp, Cpk, Pp, Ppk. And generates a Capability Six Pack Chart

• Cp

  Calculates the Cp capability index for the provided data.

• Cpk

  Calculates the Cpk capability index for the provided data.

• Pp

  Calculates the Pp capability index for the provided data.

• Ppk

  Calculates the Ppk capability index for the provided data.

Design of Experiments and ANOVA

• One-Way ANOVA

  Perform one way ANOVAs and calculate ANOVA tables, descriptive statistics tables, and confidence intervals with one function.

  Generate interval plots with the ability select confidence intervals and switch between individual and pooled standard deviations.

• Post-Hoc Testing

  When trying to determine which treatment groups are significant it is important to have tests that can evaluate statistical significance. QESuite provides the Tukey Pairwise Comparison, Fisher Least Significant Difference Method, and Duncan Multiple Range Test.

• Two-Way ANOVA

  Perform two-way ANOVAs with the ability to include or ignore interaction effects.

  Generate interaction plots and main effect plots.

• Analysis of Means (ANOM)

  Perform Analysis of Means to calculate decision limits and evaluate each mean based on the decision limits.

  Generate ANOM plot to visualize the group means and easily identify means outside of the decision limits.

• Equality of Variance Testing

  ANOVAs require the assumption that all groups are equivalent (similar). QESuite provides tests for the homogeneity of variance: Levene's Test, Bartlett's Test, F-Test.

• GRR

  Performs an ANOVA Gage R&R analysis. Generates a chart including the following graphs: Variance Components, Variation By Part, R-Chart, XBar-Chart, Variation By Operator and Part*Operator Interaction Chart.

Statistical Distributions

• *Supported Distributions*

  Exponential

  2 Parameter Exponential

  Largest Extreme Value

  Logistic

  Loglogistic

  2 Parameter Loglogistic

  2 Parameter Lognormal

  Normal

  Smallest Extreme Value

  Weibull

• Anderson-Darling

  Performs the Anderson-Darling Goodness-of-Fit test with data against the specified distribution and generates a probability plot for the data and the specified distribution. Returns the Anderson-Darling Test statistic and associated p-value

• Maximum Likelihood

  Estimates the parameters of the specified distribution using maximum likelihood estimation and generates a probability plot for the data and the specified distribution.

• Individual Distribution Identification

  Performs an Individual Distribution Identification series, estimating parameters for each supported distribution and evaluating Goodness Of Fit with the AndersonDarling test and generates a chart with the probability plots for each distribution.

Measurement Systems Analysis

• G1

  Performs a Type 1 Gage Study using the data and specified tolerance. If a reference value is included it will calculate bias(Cgk). Generates a run chart of the data.

• GRR

  Performs an ANOVA Gage R&R analysis. Generates a chart including the following graphs: Variance Components, Variation By Part, R-Chart, XBar-Chart, Variation By Operator and Part*Operator Interaction Chart.

Normality

• Anderson-Darling

  Performs the Anderson-Darling test using the normal distribution and generates a normal probability plot. Same function as previously mentioned in Distributions.

• Box-Cox Transformation

  Performs a Box-Cox transformation using either the standard Box-Cox transformation formula or the Mintab Box-Cox formula. Capable of estimating the Box-Cox transformation coefficient, lambda. Returns an array of the transformed data. Generates a normal probability plot of the transformed data.

• Chebyshev

  Evaluates the number of standard deviations the mean is from the closest spec limit to determine whether the effect of the distribution is significant. Generates a normal probability plot.

• Jarque-Bera

  Performs the Jarque-Bera (skewness-kurtosis) Test for Normality. Generates a normal probability plot.

• Kolmogorov-Smirnov

  Performs the Kolmogorov-Smirnov Test for Normality. Generates a normal probability plot.

• Lilliefors (Corrected KS) Test

  Performs the Lilliefors (Corrected KS) Test for Normality. Generates a normal probability plot.

• Ryan-Joiner

  Performs the Ryan-Joiner Test for Normality. Generates a normal probability plot.

• Shapiro-Wilk

  Performs the Shapiro-Wilk Test for Normality. Generates a normal probability plot.

• Shapiro-Wilk Royston

  Performs the Royston Expanded Shapiro-Wilk Test for Normality. Generates a normal probability plot.