Business Analytics: Multiple Comparisons in R and Excel
59mAdvanced2019-05-29
Authors

Conrad Carlberg
Writer and Consultant in Quantitative and Statistical Analysis
Course details
Statistical analysis often goes beyond simple analysis of variance (ANOVA), which tells you only if a reliable difference exists somewhere—but not specifically where. Sometimes, you may have to determine whether group A’s mean value differs reliably from the mean value of group B, or from that of group C. Multiple comparison tests are the standard for pinpointing these mean differences. In this course, Conrad Carlberg shows how to use Excel and the open-source platform R to run Tukey’s HSD test and the Scheffe ́ multiple comparison test following an ANOVA. Along the way, he discusses related concepts, such as critical values, group size, data snooping, and statistical power, and explains how they influence your choice of tests.
Skills covered
RBusiness AnalyticsMicrosoft ExcelData ScienceOpen SourceMicrosoftDeep Dive (X:Y)
Concepts
Introduction
- Pinpoint group mean differences
- Getting started
Tukey Multiple Comparisons Test
- Tukey honestly significant difference (HSD) - Overview
- Tukey - Preliminary tests in Excel
- Tukey - Test of mean differences in Excel
- Tukey - Preliminary tests in R
- Tukey - Test of mean differences in R
- Tukey - Choice of error rates
Scheff Multiple Comparisons Test
- Scheff - Overview
- Scheff - Preliminary tests in Excel
- Scheff - Contrasts in Excel
- Scheff - Calculating Psi
- Scheff - Test of mean differences in R
- Scheff - Critical values and confidence intervals
Conclusion
- Next steps