# SigmaXL

This release adds compatibility with Windows 8 and Office 2013, as well as increased functionality in the form of 4 new and 6 updated templates.

**Compatibility with Excel 2013: 32 bit and 64 bit and Excel Mac 2011**

**Automatic Assumptions Check for t-Tests and ANOVA **

- Color highlightened Text Report: Green (OK), Yellow (Warning) and Red (Serious Violation)
- Normality test check for each sample. If not possible, minimum sample size for robustness of test is checked
- Monte Carlo regression equations being utilized provided in V6.2 template
- A warning is given and a suitable Nonparametric Test is recommended in case of inadequate sample size

- Check for Outliers from sample to sample:
- Potential: Tukey's Boxplot 1.5*IQR; Likely: Tukey's Boxplot 2*IQR; Extreme: Tukey's Boxplot 3*IQR
- If outliers are present, warning and recommendation to review the data with a Boxplot and Normal Probability Plot
- If the removal of outlier(s) result in an Anderson Darling Normality Test P-Value that is >.01, a notice is given that excluding the outlier(s), the sample data are inherently normal

- Randomness (Nonparametric Runs Test)
- In case of non random sample data, warning and recommendation are suggested to review the data with a Run Chart

- Equal Variance (applicable for two or more samples)
- If all sample data are normal, F-Test or Bartlett's Test is utilized, otherwise use Levene's Test
- If the variances are unequal and the test being used is the equal variance option, then a warning is given and Welch’s test is recommended.

**Automatic Normality Check for Pearson Correlation **

- Utilizes the powerful Doornik-Hansen multivariate normality test
- Significant Pearson or Spearman correlation is highlightened in yellow
- Pearson is highlighted if the data are bivariate normal, otherwise Spearman is highlighted

**Exact Statistics for One-Way Chi-Square, Two-Way (Contingecy) Table and Nonparametric Tests **

- Exact or Monte Carlo P-Values
- Appropriate when sample size is too small for Chi-Square or Normal approximation to be valid - for example, a contingency table where more than 20% of the cells have an expected count less than 5.
- Fisher's Exact for Two-Way (Row*Column Contingency) Tables
- Exact or Monte Carlo P-Values
- Exact One-Way Chi-Square godness of fit template is an added feature now.
- Exact Nonparametric Tests: Sign, Wilcoxon, Mann-Whitney, Kruskal-Wallis, Mood's Median, and Runs Test are available

**Binary Attribute Measurement Systems Analysis (MSA)**

- User Defined "Good Part" for Type I and Type II Error Report is a new feature
- Confidence Intervals for Percent Agreement can be Wilson Score or Exact
- Confidence Interval Graphs for Percent Agreement and Fleiss' Kappa Coefficient
- Interpretation is aided by Kappa color highlightening: Green (>.9), Yellow (.7-.9) and Red (<.7)
- Effectiveness Report (treats each appraisal trial as an opportunity) and Misclassifcation Summary

**Newly added Features in Ordinal Attribute MSA **

- Confidence Interval Graphs for Percent Agreement and Kendall's Coefficients (Concordance and Correlation)
- Kendall color highlight to aid interpretation( Green/ Yellow/ Red)
- Attribute MSA Raw Data with color highlight for deviation from reference
- Effectiveness Report and Misclassification Summary

**Newly added Features in Nominal Attribute MSA **

- Confidence Interval Graphs are available now for Percent Agreement and Fleiss' Kappa Coefficient
- Kappa color highlight to aid interpretation: Green (>.9), Yellow (.7-.9) and Red (<.7)
- Effectiveness Report and Misclassification Summary are also added features

This release adds compatibility with Windows 8 and Office 2013, as well as increased functionality in the form of 4 new and 6 updated templates.

**New Statistical Templates**

- Minimum Sample Size for Robust t-Tests and ANOVA
- 1 Poisson Rate Test and Confidence Interval
- 2 Poisson Rates Test and Confidence Interval
- One-Way Chi-Square Goodness-of-Fit Test

**Updated Statistical Templates**

- 1 Sample t-Test and Confidence Interval for Mean
- 2 Sample t-Test and Confidence Interval (Compare 2 Means) with option for equal and unequal variance
- 1 Sample Chi-Square Test and CI for Standard Deviation
- 2 Sample F-Test and CI (Compare 2 Standard Deviations)
- 1 Proportion Test and Confidence Interval
- 2 Proportions Test and Confidence Interval

**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

- 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
- 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

- 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

- 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.
- 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

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

**Graphical Tools:**

**Measurement Systems Analysis: **

**Process Capability:**

**Statistical Tools: **

**Design of Experiments: **

**Reliability/Weibull Analysis: **