Learn how to draw inferences about population means across multiple groups using an ANOVA test and how to identify which ones are different using pairwise comparisons.
- What if you want to test for differences…in population means across multiple groups?…It may be processing times, dimensions,…or any characteristic that is continuous data,…such as my 100 meter sprint compared…to champions like Usain Bolt.…When comparing the performance of two or more groups,…the ANOVA test uses sample data to evaluate…and make inferences on whether population means…are statistically different or not.…And if they are different, pairwise comparisons can be made…to determine which ones are different.…
Let's run ANOVA using Minitab.…To get started, download the file…ANOVAdata.mtw from the exercise files and open it.…Here we have four groups, continuous data.…And we're interested in testing the means…across the four groups,…essentially running an ANOVA test.…But before we do that, check for normality…and equal variances.…For normality, go up to Graphs,…Probability Plot.…Since you have multiple groups, choose Multiple…and highlight those four.…
Select and run the test.…Looking at the P values, they are all high.…
Dr. 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
1. Define Phase
Overview of the Define phase3m 51s
2. Measure Phase
3. Analyze Phase
4. Improve Phase
5. Control Phase
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