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Intro to Statistics with R: Analysis of Variance (ANOVA)
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Course Description
Analysis of Variance (ANOVA) is probably one of the most popular and commonly used statistical procedures. In this course, Professor Conway will cover the essentials of ANOVA such as one-way between groups ANOVA, post-hoc tests, and repeated measures ANOVA.
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An introduction to ANOVA
FreeIn this first chapter you will learn the basic concepts of ANOVA based on the working memory training example. The difference and benefits compared to t-tests is explained, and you will see how you can compare two or more group means by engaging in ANOVA. Furthermore, you will get a deep understanding on F-tests and the corresponding distribution.
Introduction to ANOVA50 xpWorking memory experiment100 xpDifference between t-tests and ANOVA50 xpExploration of the F-test50 xpGenerate density plot of the F-distribution100 xpWhy is the F-distribution always positive?50 xpF-ratio50 xpBetween group sum of squares100 xpWithin groups sum of squares100 xpCalculating the F-ratio100 xpANOVA table50 xpA faster way: ANOVA in R100 xpSignificance of the F-ratio50 xpLevene's test100 xpDoes the assumption hold?50 xp - 2
Post-hoc analysis
FreeThe F-ratio you calculated in the previous chapter tells you if there is a significant effect somewhere across your groups, but it does not tell you which pairwise comparisons are significant. That is what the post-hoc tests explained in this chapter will do for you. Post-hoc tests such as Tukey’s and Bonferroni’s procedure allow for multiple comparisons without inflating the probability of a type I error.
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Between groups factorial ANOVA
FreeIn this final chapter on ANOVA the different concepts behind a factorial ANOVA are explained. In a Factorial ANOVA you have two independent variables and one dependent continuous variable. This allows you to look at main effects, interaction effects, and simple effects. Special attention goes to effect size, post-hoc tests, simple effects analyses and the homogeneity of variance assumption.
Introduction to factorial ANOVA50 xpStarting off50 xpData exploration with a barplot100 xpBarplot interpretation50 xpHypotheses, F-ratios and effects50 xpThe homogeneity of variance assumption100 xpHomogeneity of variance?50 xpGroups and subjects50 xpThe factorial ANOVA100 xpInterpreting the summary table50 xpPost-hoc tests and effect sizes50 xpThe interaction effect (1)100 xpThe interaction effect (2)50 xpThe interaction effect (3)50 xpThe effect sizes100 xpInterpreting etaSquared output (1)50 xpInterpreting etaSquared output (2)50 xpPairwise comparisons100 xpTukey test for the easy driving simulator50 xpTukey test for the difficult driving simulator50 xp
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