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

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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