Learn how multiple regressions can run to analyze possible relationships and develop a valid model to predict future performance in Six Sigma projects.
- Maybe you're wondering how a vehicle's speed…and driver reaction time affects stopping distance,…or maybe you're curious if there is a relationship…between height and weight…and how gender might affect it.…These are questions where there are multiple variables,…or Xs, that possibly affect an outcome or response Y.…Multiple regressions need to be run…to analyze these possible relationships…and develop a valid model to predict future performance.…Let's get started on multiple regression using Minitab.…
To get started, download from the exercise files…the worksheet MultipleRegressionData.mtw, and open it.…Let's deal with the first three columns first.…We have the Y being the Stopping Distance,…and the potential Xs would be the Speed…and Driver Reaction Time.…Let's do a regression.…Go up to Stat menu, Regression,…Regression,…and Fit Regression Model.…The Response is Stopping Distance,…and the predictors are Speed and Driver Reaction Time,…both of which are Continuous.…
We do not have any Categorical predictor X right now.…
Author
Richard Chua
Released
5/25/2017Dr. Richard Chua builds upon his Six Sigma: Green Belt, Six Sigma Foundations, and Learning Minitab courses—which are prerequisites to this course—and covers an array of topics, including measurement system analysis, hypothesis testing, response surface methods, displaying improved process capabilities, and more.
- Process flow metrics
- Measurement system analysis
- Calculating process capability
- Hypothesis testing
- Confidence intervals
- Testing for normality
- Designing, conducting, and analyzing full-factorial experiments
- Using fractional factorial experiments for screening
- Displaying improved process capability
Skill Level Intermediate
Duration
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Introduction
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Welcome1m 38s
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Certification information1m 31s
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Exercise files34s
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1. Define Phase
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Overview of the Define phase3m 51s
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2. Measure Phase
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Process flow metrics3m 34s
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Sample sizes3m 7s
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3. Analyze Phase
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Hypothesis testing road map3m 33s
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Confidence intervals3m 14s
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Test for normality2m 49s
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Compare variances5m 16s
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T-tests6m 4s
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ANOVA3m 55s
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Contingency tables6m 49s
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Nonparametric tests6m 49s
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Correlation3m 45s
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Linear regression4m 38s
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Multiple regression5m 5s
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4. Improve Phase
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Full-factorial experiments9m 19s
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DOE with curvature6m 27s
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Response surface methods8m 37s
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5. Control Phase
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SPC chart selection4m 46s
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SPC chart analysis5m 1s
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Conclusion
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Next steps56s
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Video: Multiple regression