Sigma XL Software Offer (For Six Sigma Students Only)
Course
Online
Description
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Type
Course
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Level
Intermediate
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Methodology
Online
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Class hours
12h
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Duration
1 Year
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Start date
Different dates available
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Online campus
Yes
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Support service
Yes
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Virtual classes
Yes
Simplify the Six Sigma statistics gathering process with the SigmaXL Excel add-in. This unique tool provides powerful statistical and graphical analysis tools that allow students to measure, analyse, improve and control processes.
The Lean Six Sigma framework relies on collecting accurate data and performing advances statistical analysis to benchmark existing processes and precisely calculate potential the value of proposed improvements.
Facilities
Location
Start date
Start date
About this course
KEY LEARNING POINTS
What's New in SigmaXL Version 8.0:
Templates and Calculators
Descriptive Statistics
Analysis of Means (ANOM) Charts
Multiple Comparisons (Post-Hoc)
Chi-Square Tests & Table Associations
SigmaXL is a cost-effective option for students who want to simplify the statistical gathering and analysis that makes up the Six Sigma methodology. This offer is available exclusively to our students who have already enrolled on an approved Six Sigma course.
Lean Six Sigma tools tend to be expensive, inflexible and extremely complicated – particularly for students just starting to learn the basics of the process improvement methodology. Although extremely powerful, SigmaXL is much easier for learners to get to grips with, particularly as it uses the familiar Microsoft Excel environment as its framework.
Reviews
Subjects
- Six Sigma
- Statistics
- Design
- Confidence Training
- Probability
- Category
- Random
- Date
- Transpose Data
- Across Rows
- Unstack Columns
- Standardize Data
- Random Number Generator
Course programme
Data Manipulation
- Subset by Category, Random, Number, or Date
- Transpose Data
- Stack Subgroups Across Rows
- Stack and Unstack Columns
- Standardize Data
- Normal
- Uniform (Continuous & Integer)
- Lognormal
- Weibull
- Triangular
- Remove Blank Rows and Columns
- Change Text Data Format to Numeric
- Box-Cox Transformation
DMAIC & DFSS Templates
- Team/Project Charter
- SIPOC Diagram
- Flowchart Toolbar
- Data Measurement Plan
- Cause & Effect (Fishbone) Diagram and Quick Template
- Failure Mode & Effects Analysis (FMEA) with RPN Sort
- Quality Function Deployment (QFD)
- Pugh Concept Selection Matrix
- Control Plan
- Takt Time Calculator
- Value Analysis/Process Load Balance
- Value Stream Mapping
- Pareto Chart
- Histogram
- Run Chart
- Sample Size Discrete and Continuous
- Minimum Sample Size for Robust t-Tests and ANOVA
- 1 Sample t-Test and Confidence Interval for Mean
- 2 Sample t-Test and Confidence Interval (Compare 2 Means)
- 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 Proportion Tests and Confidence Interval
- 1 Poisson Rate Test and Confidence Interval
- 2 Poisson Rates Test and Confidence Interval
- One-Way Chi-Square and Goodness of Fit Test
- Normal, Lognormal, Exponential, Weibull
- Binomial, Poisson, Hypergeometric
- Gage R&R Study with Multi-Vari Analysis
- Attribute Gage R&R (Attribute Agreement Analysis)
Process Capability & Confidence Intervals
DOE Templates
- 2 to 5 Factors
- 2-Level Full and Fractional-Factorial designs
- Main Effects & Interaction Plots
- 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, replicates
- 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
- 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
- Histogram, Normal Probability Plot and Normality Test
- Capability Report (Cp, Cpk, Pp, Ppk, Cpm, ppm, %)
- Control Chartsy
- 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
- Nonnormal Process Capability Indices: Z-Score (Cp, Cpk, Pp, Ppk) and Percentile (ISO) Method (Pp, Ppk)
- All valid distributions and transformations reported with histograms, curve fit and probability plots
- Within Appraiser Agreement, Each Appraiser vs Standard Agreement, Each Appraiser vs Standard Disagreement, Between Appraiser Agreement, All Appraisers vs Standard Agreement; Fleiss’ kappa
- P-values turn red when results are significant (p-value < alpha)
- Descriptive Statistics including Anderson-Darling Normality test, Skewness and Kurtosis with p-values
- Confidence Intervals
- 1 Sample t-test
- 2 Sample t-test, Paired t-test
- Reports AD Normality, F-test and Levenes 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 Welchs ANOVA)
- Correlation Matrix (Pearson and Spearmans Rank Correlation)
- 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
- Fit Intercept is optional
- 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.
- Mixing Down to a CD
Nonparametric Tests:
- 1 Sample Sign and 1 Sample Wilcoxon
- 2 Sample Mann-Whitney
- Kruskal-Wallis and Moods Median Test
- Kruskal-Wallis and Moods include a graph of Group Medians and 95% Median Confidence Intervals
- Runs Test
- 1 Sample t-Test, 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
- 2 to 5 Factors, 2-Level Full and Fractional-Factorial designs
- Automatic update to Pareto of Coefficients
- Easy to use, ideal for training part
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
Response Surface Designs
- 2 to 5 Factors
- Central Composite and Box-Behnken Designs
- Easy to use design selection sorted by number of runs
- Control Chart Selection Tool
- Individuals
- X-Bar & R, X-Bar & S
- I-MR-R, I-MR-S (Between/Within)
- P, NP, C, U
- P and U (Laney) to handle overdispersion
- Control charts include a report on tests for special causes. Special causes are also labeled on the control chart data point. Set defaults to apply any or all of Tests 1-8.l
- Process Capability report (Pp, Ppk, Cp, Cpk) is available for I, I-MR, X-Bar & R, X-bar & S charts.Add data to existing charts for operator ease of use!
- Advanced Control Limit options: Subgroup Start and End; Historical Groups (e.g. split control limits to demonstrate before and after improvement)
- Exclude data points for control limit calculation
- Add comment to data point for assignable cause
- 1, 2 Sigma Zone Lines
- Box-Cox and Johnson Transformations
- 16 Nonnormal distributions supported (see Process Capability)
- Individuals chart of original data with percentile based control limits
- Individuals/Moving Range chart for normalized data with optional tests for special causes
Complete and Right Censored data
- Complete and Right Censored data
- Least Squares and Maximum Likelihood
- Output includes percentiles with confidence intervals, survival probabilities, and Weibull probability plot.
Sigma XL Software Offer (For Six Sigma Students Only)