Archive:Advanced ANOVA/One-way ANOVA

File:Wikademia.logo.png Resource type: this resource contains a tutorial or tutorial notes. Template:50%done This tutorial teaches understanding and use of one-way ANOVA as a statistical technique for testing mean differences between three or more independent groups. Practical exercises are based on using SPSS.

Introduction

• Unit outline (updated - to upload/link)
• [[../Assessment/]]

General steps

1. Establish hypothesis/hypotheses
2. Examine [[../Assumptions|assumptions]]
3. Examine descriptive statistics, particularly the four moments (M, SD, Skewness, Kurtosis) overall, and also for each group
4. Examine graphs, e.g.,:
   • Histograms
   • Normal probability plot
   • Error-bar graph
5. Conduct inferential test (ANOVA) and interpret significance of F
6. Conduct follow-up tests (planned contrasts or post-hoc tests) if F is significant
7. Calculate and interpret effect sizes
   • Eta-square (omnibus - equivalent to R²)
   • Standardised mean effect size (difference b/w two means)

Visual ANOVA

• Understanding ANOVA Visually (may require viewing with Internet Explorer)
• Under what conditions would F be the smallest?
• Under what conditions would F be the largest?
• Now explore the same ideas with this more advanced Visualisation Tool for One-way and Two-way ANOVA Applet

Error bar graphs

Error-bar graph showing mean pulse rates and 95% confidence intervals by exercise level.

• Use any dataset
• Conduct a one-way ANOVA and graphically present the means and confidence intervals using an Error Bar Graph - is this error bar chart consistent with the statistical results?
  • Why?
  • Why not?

Data

1. AQUES.sav
2. Motiv.sav

See also

• Analysis of variance/Data analysis tutorial (3rd year tutorial)
• Analysis of variance (Wikipedia)

External links

• ANOVA (ucspace)
  • One-way ANOVA example writeup