christine p. dancey and john reidy statistics without

Statistics without Maths for Psychology

Christine P. Dancey and John Reidy

Eighth Edition

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Statistics Without Maths for Psychology8th edition PDF ebook

Table of Contents

Front Cover

Half Title Page

Title Page

Copyright Page

Brief Contents

Contents

Preface��

Publisher's acknowledgements

1 Variables and research design��Chapter overview��

1.1 Why teach statistics without mathematicalformulae?��

1.2 Variables��

1.3 Levels of measurement��

1.4 Research designs��

1.5 Between-participants and within-participantsdesigns��

Summary��

Multiple choice questions��

References��

Answers to multiple choice questions��

2 Introduction to SPSS��Chapter overview��

2.1 Basics��

2.2 Starting SPSS��

2.3 Working with data��

2.4 Data entry��

2.5 Saving your data��

2.6 Inputting data for between-participants and within-participantsdesigns��

2.7 Within-participants designs��

Summary��

SPSS exercises��

3 Descriptive statistics��

Table of Contents

Chapter overview��

3.1 Samples and populations��

3.2 Measures of central tendency��

3.3 Sampling error��

SPSS: obtaining measures of centraltendency��

3.4 Graphically describing data��

SPSS: generating graphicaldescriptives��

3.5 Scattergrams��

SPSS: generating scattergrams��

3.6 Sampling error and relationships betweenvariables��

3.7 The normal distribution��

3.8 Variation or spread ofdistributions��

SPSS: obtaining measures ofvariation��

3.9 Other characteristics ofdistributions��

3.10 Non-normal distributions��

SPSS: displaying the normal curve onhistograms��

3.11 Writing up your descriptivestatistics��

Summary��



References��


4 Probability, sampling anddistributions��


4.1 Probability��

4.2 The standard normal distribution��

4.3 Applying probability to research��

4.4 Sampling distributions��

4.5 Confidence intervals and the standard

Table of Contents

error��SPSS: obtaining confidence intervals��

4.6 Error bar charts��

4.7 Overlapping confidence intervals��

SPSS: generating error bar charts��

4.8 Confidence intervals around otherstatistics��

Summary��



References��


5 Hypothesis testing and statisticalsignificance��


5.1 Another way of applying probabilities to research: hypothesistesting��

5.2 Null hypothesis��

5.3 Logic of null hypothesis testing��

5.4 The significance level��

5.5 Statistical significance��

5.6 The correct interpretation of thep-value��

5.7 Statistical tests��

5.8 Type I error��

5.9 Type II error��

5.10 Why set at 0.05?��

5.11 One-tailed and two-tailedhypotheses��

5.12 Assumptions underlying the use of statisticaltests��

SPSS: Statistics Coach��

Summary��



References��


6 Correlational analysis: Pearson's r

Table of Contents


6.1 Bivariate correlations��

SPSS: bivariate correlations - Pearson's r

SPSS: obtaining a scattergram matrix��

6.2 First- and second-ordercorrelations��

SPSS: partial correlations - Pearson's r

6.3 Patterns of correlations��

Summary��

SPSS exercise��


References��


7 Analyses of differences between two conditions: thet-test��


7.1 Analysis of two conditions��

SPSS: for an independent t-test��

SPSS: two samples repeated-measures design - paired t-test

Summary��

SPSS exercise��


References��


8 Issues of significance��Chapter overview��

8.1 Criterion significance levels��

8.2 Effect size��

8.3 Power��

8.4 Factors influencing power��

8.5 Calculating power��

8.6 Confidence intervals��

Summary��


References��


9 Measures of association��

Table of Contents


9.1 Frequency (categorical) data��

9.2 One-variable x2 or goodness-of-fit test

SPSS: one-variable x2

SPSS: one-variable x2 - using frequencies different from those expected underthe null hypothesis

9.3 x2 test for independence: 2 * 2

SPSS: 2 * 2x2

9.4 x2 test of independence: r * c

Summary��



References��


10 Analysis of differences between three or moreconditions��


10.1 Visualising the design��

10.2 Meaning of analysis of variance��

SPSS: performing a one-way ANOVA��

10.3 Descriptive statistics��

10.4 Planned comparisons��

10.5 Controlling for multipletesting��

10.6 Post-hoc tests��

10.7 Repeated-measures ANOVA��

SPSS: instructions for repeated-measuresANOVA��

Summary��



References��


11 Analysis of variance with more than oneIV��


11.1 Introduction��

11.2 Sources of variance��

Table of Contents

11.3 Designs suitable for factorialANOVA��

11.4 ANOVA terminology��

11.5 Two between-participants independentvariables��

SPSS: analysis of two between-participantsfactors��

11.6 Two within-participantsvariables��

SPSS: ANOVA with two within-participantsfactors��

11.7 One between- and one within-participantsvariable��

SPSS: ANOVA with one between-participants factor and one within-participantsfactor��

Summary��



References��


12 Regression analysis��Chapter overview��

12.1 The purpose of linearregression��

SPSS: drawing the line of best fit��

SPSS: linear regression analysis��

12.2 Multiple regression��

Summary��



References��


13 Analysis of three or more groups partialling out effects of acovariate��


SPSS: obtaining a chart of regressionlines��

13.1 Pre-existing groups��

Table of Contents

13.2 Pretest-posttest designs

SPSS: obtaining output for an ANCOVA��

Summary��

SPSS exercise��


References��


14 Introduction to factor analysis��Chapter overview��

14.1 What is the purpose of factoranalysis?��

14.2 The two main types of factoranalysis��

14.3 Use of factor analysis inpsychometrics��

14.4 Visualising factors��

14.5 Conceptualising factor analysis��

14.6 Naming the factors��

14.7 Loadings of variables onfactors��

14.8 The correlational matrix��

14.9 The unrotated and rotatedmatrices��

14.10 Plotting the variables in factorspace��

14.11 Rotating the matrix��

14.12 Steps taken in performing a factoranalysis��

14.13 Use of factors or components in furtheranalyses��

14.14 The meaning of negativeloadings��

SPSS: factor analysis - principal components analysis

Summary��


References��


15 Introduction to multivariate analysis of variance

Table of Contents

(MANOVA)��Chapter overview��

15.1 Multivariate statistics��

15.2 Why use multivariate analyses ofvariance?��

15.3 Multivariate analysis ofvariance��

15.4 Logic of MANOVA��

15.5 Assumptions of MANOVA��

15.6 Which F-value?��

15.7 Post-hoc analyses of individualDVs��

15.8 Correlated DVs��

15.9 How to write up these analyses��

SPSS: conducting MANOVA with one between-participants IV and twoDVs��

15.10 Within-participants designs��

SPSS: one within-participants IV and twoDVs��

Summary��



References��

Recommended texts��


16 Non-parametric statistics��Chapter overview��

16.1 Alternative to Pearson's r: Spearman's rho

SPSS: correlational analysis - Spearman's rho

SPSS exercise��

16.2 Alternatives to the t-test: Mann-Whitney and Wilcoxon

SPSS: two-sample test for independent groups - Mann-Whitney

SPSS exercise��

SPSS: two-sample test for repeated measures - Wilcoxon

SPSS exercise��

16.3 Alternatives to ANOVA��

SPSS: independent samples test for more than two conditions - Kruskal-Wallis

SPSS exercise��

Table of Contents

SPSS: repeated-measures test for more than two conditions - Friedman's test

SPSS exercise��

Summary��


References��


Answers to activities and SPSSexercises��

Appendix 1: Table of z-scores and the proportion of the standard normaldistribution falling above and below eachscore��

Appendix 2: Table r to zr��

Index��

Back Cover

christine p. dancey and john reidy statistics without

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