Summary
Contents
Subject index
Understanding and Using Statistics in Psychology takes the fear out of psychological statistics to help students understand why statistics are carried out, how to choose the best test, how to carry out the tests, and then perform the analysis in SPSS. Emphasizing the place of statistical analysis in the process of conducting research, from design to report writing, this accessible and straightforward guide takes a non-technical approach, encouraging the reader to understand why a particular test is being used and what the results mean in the context of a psychological study. The focus is on meaning and understanding rather than numerical calculation.
Introducing Analysis of Variance
Introducing Analysis of Variance
What's in This Chapter?
- What is ANOVA?
- Calculating ANOVA
- Post hoc testing
- Using SPSS
Key Terms
alpha inflation
analysis of variance
Bonferroni correction
box and whisker plot
confidence interval
degrees of freedom
effect size
error
factors
F-ratio
histograms
homogeneity of variance
mean squares
normal distribution
outcome variable
partition
post hoc tests
predictor variables
regression
statistical significance
sums of squares
t-test
type I error
Introduction
In this chapter we are going to introduce the ideas behind analysis of variance (ANOVA). ANOVA is a very flexible and general technique, and the principles can be applied to a wide range of statistical tests (including many that we have already encountered in this book). ANOVA has a wide range of applications, but many of those applications make some tricky assumptions about the data. Unlike the assumptions that we have encountered so far, which didn't make much difference as long as they ...
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