SigmaXL

SigmaXLŽ Version 6.0 Feature List Summary

Excel 2007 Ribbon

Menu Layout: Classical or DMAIC

Worksheet Manager**

Data Manipulation:

Subset by Category, Number, Date or Random
Stack Subgroups Across Rows
Stack and Unstack Columns
Standardize Data
Normal Random Number Generator
- Normal
- Uniform (Continuous & Integer)**
- Lognormal**
- Weibull**
- Triangular**
Box-Cox Transformation

Templates & Calculators:

DMAIC & DFSS Templates
- Team/Project Charter
- SIPOC Diagram
- Flowchart Toolbar
- Data Measurement Plan
- Cause & Effect (Fishbone) Diagram and Quick Template
- Cause & Effect (XY) Matrix
- Failure Mode & Effects Analysis (FMEA)
- Quality Function Deployment (QFD)
- Pugh Concept Selection Matrix
- Control Plan
Lean Templates
- Takt Time Calculator
- Value Analysis/Process Load Balance
- Value Stream Mapping**
Graphical Templates
- Pareto Chart
- Histogram
- Run Chart
Statistical Templates
- Sample Size – Discrete and Continuous
- 1 Sample t Confidence Interval for Mean**
- 2 Sample t-Test (Assume Equal and Unequal Variances)**
- 1 Sample Confidence Interval for Standard Deviation
- 2 Sample F-Test (Compare 2 StDevs)**
- 1 Proportion Confidence Interval (Normal and Exact)
- 2 Proportions Test & Fisher’s Exact**
Probability Distribution Calculators**
- Normal, Lognormal, Exponential, Weibull
- Binomial, Poisson, Hypergeometric
MSA Templates
- Gage R&R Study – with Multi-Vari Analysis
- Attribute Gage R&R (Attribute Agreement Analysis)
Process Sigma Level – Discrete and Continuous
Process Capability & Confidence Intervals
DOE Templates
- 2 to 5 Factors
- 2-Level Full and Fractional-Factorial designs
- Main Effects & Interaction Plots
Control Chart Templates
- Individuals
- C-Chart

Graphical Tools:

Basic and Advanced (Multiple) Pareto Charts
EZ-Pivot/Pivot Charts: Easily create Pivot Tables and Charts
Basic Histogram
Multiple Histograms and Descriptive Statistics (includes Confidence Interval for Mean and StDev., and Anderson-Darling Normality Test)
Multiple Histograms and Process Capability (Pp, Ppk, Cpm, ppm, %)
Multiple Boxplots, Dotplots
Run Charts (with Nonparametric Runs Test allowing you to test for Clustering, Mixtures, Lack of Randomness, Trends and Oscillation)
Overlay Run Chart
Multiple Normal Probability Plots (with 95% confidence intervals to ease interpretation of normality/non-normality)
Multi-Vari Charts
Scatter Plots (with linear regression and optional 95% confidence intervals and prediction intervals)
Scatter Plot Matrix

Measurement Systems Analysis:

Create Gage R&R (Crossed) Worksheet:
- Generate worksheet with user specified number of parts, operators
Analyze Gage R&R (Crossed)
- ANOVA, %Total, %Tolerance (with upper and/or lower specifications), %Process, Variance Components, Number of Distinct Categories
- Gage R&R Multi-Vari and X-bar R Charts
- Confidence Intervals for %Total, %Tolerance, %Process and Standard Deviations
- Handles unbalanced data
Alirtibute MSA (Binary)
- Any number of samples, appraisers and replicates
- Within Appraiser Agreement, Each Appraiser vs Standard Agreement, Each Appraiser vs Standard Disagreement, Between Appraiser Agreement, All Appraisers vs Standard Agreement; Fleiss' kappa

Process Capability:

Multiple Histograms and Process Capability
Capability Combination Report for Individuals/Subgroups:
- Histogram, Normal Probability Plot and Normality Test
- Capability Report (Cp, Cpk, Pp, Ppk, Cpm, ppm, %)
- Control Charts
Capability Combination Report for Nonnormal Data (Individuals)**
- Box-Cox Transformation (includes an automatic threshold option so that data with negative values can be transformed)
- Johnson Transformation
- Distributions supported: Half-Normal, Lognormal (2 & 3 parameter), Exponential (1 & 2), Weibull (2 & 3), Beta (2 & 4), Gamma (2 & 3), Logistic, Loglogistic (2 & 3), Largest Extreme Value, Smallest Extreme Value
- Automatic Best Fit based on AD p-value
- Nonnormal Process Capability Indices: Z-Score (Cp, Cpk, Pp, Ppk) and Percentile (ISO) Method (Pp, Ppk)
Distribution Fitting Report**
- All valid distributions and transformations reported with histograms, curve fit and probability plots
- Sorted by AD p-value

Statistical Tools:

P-values turn red when results are significant (p-value < alpha)
Descriptive Statistics including Anderson-Darling Normality test, Skewness and Kurtosis with p-values
1 Sample t-test and confidence intervals
Paired t-test, 2 Sample t-test
2 Sample comparison tests:
- Reports AD Normality, F-test and Levene’s for variance, t-test assuming equal and unequal variance, Mann-Whitney test for medians.
- Recommended tests are highlighted based on sample size, normality, and variance
One-Way ANOVA and Means Matrix
Two-Way ANOVA (Balanced and Unbalanced)
Equal Variance Tests (Bartlett, Levene and Welch’s ANOVA)
Correlation Matrix (Pearson and Spearman’s Rank Correlation)
Multiple Linear Regression:
- Accepts continuous and/or categorical (discrete) predictors
- Interactive Predicted Response Calculator with 95% Confidence Interval and 95% Prediction Interval
- Residual Plots: histogram, normal probability plot, residuals vs. time, residuals vs. predicted and residuals vs. X factors
- Residual types include Regular, Standardized, Studentized (Deleted t) and Cook's Distance (Influence), Leverage and DFITS
- Highlight of significant outliers in residuals
- Durbin-Watson Test for Autocorrelation in Residuals with p-value
- ANOVA report for categorical predictors
- Pure Error and Lack-of-Fit report
- Collinearity Variance Inflation Factor (VIF) and Tolerance report
- Fit Intercept is optional
Binary and Ordinal Logistic Regression
- Powerful and user-friendly logistic regression.
- Report includes a calculator to predict the response event probability for a given set of input X values.
- Categorical (discrete) predictors can be included in the model in addition to continuous predictors.
- Model summary and goodness of fit tests include Likelihood Ratio Chi-Square, Pseudo R-Square, Pearson Residuals Chi-Square, Deviance Residuals Chi-Square, Observed and Predicted Outcomes – Percent Correctly Predicted.
- Stored data includes Event Probabilities, Predicted Outcome, Observed-Predicted, Pearson Residuals, Standardized Pearson Residuals, and Deviance Residuals.
Chi-Square Test (Stacked Column data and Two-Way Table data)
Nonparametric Tests:
- 1 Sample Sign and 1 Sample Wilcoxon
- 2 Sample Mann-Whitney
- Kruskal-Wallis and Mood’s Median Test
- Kruskal-Wallis and Mood’s include a graph of Group Medians and 95% Median Confidence Intervals
- Runs Test
Power and Sample Size Calculators for:
- 1 and 2 Sample t-Test
- One-Way ANOVA
- 1 Proportion Test, 2 Proportions Test
- The Power and Sample Size Calculators allow you to solve for Power (1 – Beta), Sample Size, or Difference (specify two, solve for the third).
Power and Sample Size Chart. Quickly create a graph showing the relationship between Power, Sample Size and Difference.

Design of Experiments:

Generate 2-Level Factorial and Plackett-Burman Screening Designs
- User-friendly dialog box
- 2 to 19 Factors; 4,8,12,16,20 Runs
- Unique “view power analysis as you design”
- Randomization, Replication, Blocking and Center Points
Basic DOE Templates
- 2 to 5 Factors, 2-Level Full and Fractional-Factorial designs
- Automatic update to Pareto of Coefficients
- Easy to use, ideal for training
Main Effects & Interaction Plots
Analyze 2-Level Factorial and Plackett-Burman Screening Designs
- Used in conjunction with Recall Last Dialog, it is very easy to iteratively remove terms from the model
- Interactive Predicted Response Calculator with 95% Confidence Interval and 95% Prediction Interval.
- ANOVA report for Blocks, Pure Error, Lack-of-Fit and Curvature
- Collinearity Variance Inflation Factor (VIF) and Tolerance report
- Residual plots: histogram, normal probability plot, residuals vs. time, residuals vs. predicted and residuals vs. X factors
- Highlight of significant outliers in residuals
- Durbin-Watson Test for Autocorrelation
Contour & 3D Surface Plots**
Response Surface Designs**
- 2 to 5 Factors
- Central Composite and Box-Behnken Designs
- Easy to use design selection sorted by number of runs

Reliability/Weibull Analysis:

Weibull Analysis
- Complete and Right Censored data
- Least Squares and Maximum Likelihood
- Output includes percentiles with confidence intervals, survival probabilities, and Weibull probability plot.

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