A Student's Guide to Analysis of VarianceIn the investigation of human behaviour, statistical techniques are employed widely in the social sciences. Whilst introductory statistics courses cover essential techniques, the complexities of behaviour demand that more flexible and comprehensive methods are also employed. Analysis of Variance (ANOVA) has become one of the most common of these and it is therefore essential for both student and researcher to have a thorough understanding of it. A Student's Guide to Analysis of Variance covers a range of statistical techniques associated with ANOVA, including single and multiple factor designs, various follow-up procedures such as post-hoc tests, and how to make sense of interactions. Suggestions on the best use of techniques and advice on how to avoid the pitfalls are included, along with guidelines on the writing of formal reports. Introductory level topics such as standard deviation, standard error and t-tests are revised, making this book an invaluable aid to all students for whom ANOVA is a compulsory topic. It will also serve as a useful refresher for the more advanced student and practising researcher. |
Contents
Averages measures of dispersal and the ttest | 9 |
Using variance to test hypotheses | 30 |
advanced topics | 62 |
Following up a onefactor betweensubjects ANOVA | 82 |
Calculating F ratios for onefactor withinsubjects | 110 |
An introduction to factorial designs and interactions | 134 |
Calculating F ratios for twofactor betweensubjects | 153 |
Following up a twofactor betweensubjects ANOVA | 172 |
selected data | 189 |
Interpreting twofactor mixed and withinsubjects | 194 |
Interpreting a threefactor ANOVA | 211 |
Summary and frequently asked questions | 224 |
Writing up the results of Analysis | 233 |
A3 Specimen results section for the letter deletion | 238 |
Notes 258 | |
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Common terms and phrases
A₁ A₂ Analysis of Variance ANOVA table assumption B₁ B₂ basic ratio between-group Sum between-group variance Bonferroni adjustment cell means Chapter compared contrast analysis critical value degrees of freedom equation example data experiment experimental error expertise F ratio factorial design familywise Type Figure follow-up tests grand mean graph Hence independent variable interaction plot Level A2 level means Mean Square mnemonic non-significant novices null hypothesis number of levels number of scores number of subjects outcome pair of means pairwise comparisons performance planned comparisons population position type possible post-hoc tests prediction problem random errors random positions real positions sample means shows significance level significant difference significant effect significant main effect simple main effects SOURCE Sum SSBETWEEN SSTOTAL SSWITHIN standard deviations statistical tests Sum of Squares t-test test the significance three-way interaction treatment effects Tukey test two-factor two-tailed Type I Error within-group Sum within-group variance within-subjects design ΣΥ
References to this book
Discovering Statistics Using SPSS for Windows: Advanced Techniques for the ... Andy P. Field No preview available - 2000 |
ANOVA for the Behavioural Sciences Researcher Rudolf N. Cardinal,Michael R. F. Aitken No preview available - 2006 |