### Additional Information

#### Book Details

### Abstract

*Introduction to SPSS in Psychology*, 7th edition is the essential step by step guide to SPSS for students taking their first course in statistics. This well-established text provides a clear and comprehensive coverage of how to carry out statistical analyses using SPSS. Full colour SPSS screenshots, clear explanation and a wide ranging coverage make it the perfect companion for students who want to be able to analyse data with confidence.

### Table of Contents

Section Title | Page | Action | Price |
---|---|---|---|

Cover | Cover | ||

Half-Title Page | i | ||

Title Page | iii | ||

Copyright Page | iv | ||

Summary of contents | v | ||

Contents | vii | ||

Guided tour | xxii | ||

Introduction | xxvi | ||

Acknowledgements | xxix | ||

Part 1 Introduction to SPSS in Psychology | 1 | ||

1 Brief introduction to statistics | 3 | ||

Overview | 3 | ||

1.1 Basic statistical concepts essential in SPSS analyses | 4 | ||

1.2 Basic research designs: comparative versus correlational designs | 4 | ||

1.3 Different types of variables in statistics | 7 | ||

1.4 Descriptive and inferential statistics compared | 9 | ||

1.5 Related versus unrelated designs | 11 | ||

1.6 Quick summaries of statistical analyses | 12 | ||

1.7 Which procedure or test to use | 12 | ||

2 Basics of SPSS data entry and statistical analysis | 17 | ||

Overview | 17 | ||

2.1 What is SPSS? | 18 | ||

2.2 Accessing SPSS | 18 | ||

2.3 Entering data | 20 | ||

2.4 Moving within a window with the mouse | 21 | ||

2.5 Moving within a window using the keyboard keys with the mouse | 21 | ||

2.6 Saving data to memory device | 22 | ||

2.7 Opening up a data file | 23 | ||

2.8 Using â€˜Variable Viewâ€™ to create and label variables | 24 | ||

2.9 More on â€˜Data Viewâ€™ | 26 | ||

2.10 Simple statistical calculation with SPSS | 28 | ||

2.11 SPSS output | 29 | ||

Summary of SPSS steps for a statistical analysis | 29 | ||

Part 2 Descriptive statistics | 31 | ||

3 Describing variables tabularly | 33 | ||

Overview | 33 | ||

3.1 What are tables? | 34 | ||

3.2 When to use tables | 35 | ||

3.3 When not to use tables | 35 | ||

3.4 Data requirements for tables | 35 | ||

3.5 Problems in the use of tables | 35 | ||

3.6 Data to be analysed | 36 | ||

3.7 Entering summarised categorical or frequency data by weighting | 36 | ||

3.8 Percentage frequencies | 38 | ||

3.9 Interpreting the output | 38 | ||

3.10 Reporting the output | 39 | ||

Summary of SPSS steps for frequency tables | 39 | ||

4 Describing variables diagrammatically | 40 | ||

Overview | 40 | ||

4.1 What are diagrams? | 41 | ||

4.2 When to use diagrams | 42 | ||

4.3 When not to use diagrams | 42 | ||

4.4 Data requirements for diagrams | 42 | ||

4.5 Problems in the use of diagrams | 42 | ||

4.6 Data to be analysed | 43 | ||

4.7 Entering summarised categorical or frequency data by weighting | 43 | ||

4.8 Pie diagram of category data | 46 | ||

4.9 Adding labels to the pie diagram and removing the legend and label | 47 | ||

4.10 Changing the colour of a pie-diagram slice to a black-and-white pattern | 49 | ||

4.11 Bar chart of category data | 51 | ||

4.12 Histograms | 52 | ||

Summary of SPSS steps for charts | 54 | ||

5 Describing variables numerically: Averages, variation and spread | 55 | ||

Overview | 55 | ||

5.1 What are averages, variation and spread? | 56 | ||

5.2 When to use averages, variation and spread | 60 | ||

5.3 When not to use averages, variation and spread | 60 | ||

5.4 Data requirements for averages, variation and spread | 60 | ||

5.5 Problems in the use of averages, variation and spread | 60 | ||

5.6 Data to be analysed | 61 | ||

5.7 Entering the data | 61 | ||

5.8 Mean, median, mode, standard deviation, variance and range | 62 | ||

5.9 Interpreting the output | 63 | ||

5.10 Other features | 63 | ||

5.11 Reporting the output | 64 | ||

Summary of SPSS steps for descriptive statistics | 64 | ||

6 Shapes of distributions of scores | 65 | ||

Overview | 65 | ||

6.1 What are the different shapes of scores? | 66 | ||

6.2 When to use histograms and frequency tables of scores | 69 | ||

6.3 When not to use histograms and frequency tables of scores | 70 | ||

6.4 Data requirements for using histograms and frequency tables of scores | 70 | ||

6.5 Problems in using histograms and frequency tables of scores | 70 | ||

6.6 Data to be analysed | 70 | ||

6.7 Entering the data | 71 | ||

6.8 Frequency tables | 71 | ||

6.9 Interpreting the output | 72 | ||

6.10 Histograms | 73 | ||

6.11 Interpreting the output | 74 | ||

Summary of SPSS steps for frequency distributions | 75 | ||

7 Relationships between two or more variables Tables | 76 | ||

Overview | 76 | ||

7.1 What tables are used to show relationships between variables? | 77 | ||

7.2 When to use tables to show relationships between variables | 79 | ||

7.3 When not to use tables to show relationships between variables | 79 | ||

7.4 Data requirements for tables to show relationships between variables | 80 | ||

7.5 Problems in the use of tables to show relationships between variables | 80 | ||

7.6 Data to be analysed | 80 | ||

7.7 Entering the data | 81 | ||

7.8 Weighting the data | 82 | ||

7.9 Crosstabulation with frequencies | 83 | ||

7.10 Displaying frequencies as a percentage of the total number | 84 | ||

7.11 Displaying frequencies as a percentage of the column total | 85 | ||

Summary of SPSS steps for contingency tables | 85 | ||

8 Relationships between two or more variables Diagrams | 86 | ||

Overview | 86 | ||

8.1 What diagrams are used to show relationships between variables? | 87 | ||

8.2 When to use diagrams to show relationships between variables | 90 | ||

8.3 When not to use diagrams to show relationships between variables | 90 | ||

8.4 Data requirements for diagrams to show relationships between variables | 90 | ||

8.5 Problems in the use of diagrams to show relationships between variables | 91 | ||

8.6 Data to be analysed | 91 | ||

8.7 Entering the data | 92 | ||

8.8 Weighting the data | 93 | ||

8.9 Compound (stacked) percentage bar chart | 94 | ||

8.10 Compound (clustered) bar chart | 96 | ||

Summary of SPSS steps for bar charts | 98 | ||

9 Correlation coefficients: Pearsonâ€™s correlation and Spearmanâ€™s rho | 99 | ||

Overview | 99 | ||

9.1 What is a correlation coefficient? | 100 | ||

9.2 When to use Pearson and Spearman rho correlation coefficients | 103 | ||

9.3 When not to use Pearson and Spearman rho correlation coefficients | 103 | ||

9.4 Data requirements for Pearson and Spearman rho correlation coefficients | 103 | ||

9.5 Problems in the use of correlation coefficients | 104 | ||

9.6 Data to be analysed | 104 | ||

9.7 Entering the data | 105 | ||

9.8 Pearsonâ€™s correlation | 105 | ||

9.9 Interpreting the output | 106 | ||

9.10 Spearmanâ€™s rho | 107 | ||

9.11 Interpreting the output | 107 | ||

9.12 Scatter diagram | 108 | ||

9.13 Interpreting the output | 110 | ||

9.14 Scattergram with more than one case with the same two values | 110 | ||

Summary of SPSS steps for correlation | 112 | ||

10 Regression: Prediction with precision | 113 | ||

Overview | 113 | ||

10.1 What is simple regression? | 114 | ||

10.2 When to use simple regression | 116 | ||

10.3 When not to use simple regression | 116 | ||

10.4 Data requirements for simple regression | 116 | ||

10.5 Problems in the use of simple regression | 117 | ||

10.6 Data to be analysed | 117 | ||

10.7 Entering the data | 118 | ||

10.8 Simple regression | 118 | ||

10.9 Interpreting the output | 119 | ||

10.10 Regression scatterplot | 120 | ||

10.11 Interpreting the output | 123 | ||

Summary of SPSS steps for simple regression | 124 | ||

Part 3 Significance testing and basic inferential tests | 125 | ||

11 Related t-test: Comparing two samples of correlated/related/paired scores | 127 | ||

Overview | 127 | ||

11.1 What is the related t-test? | 128 | ||

11.2 When to use the related t-test | 130 | ||

11.3 When not to use the related t-test | 131 | ||

11.4 Data requirements for the related t-test | 131 | ||

11.5 Problems in the use of the related t-test | 131 | ||

11.6 Data to be analysed | 132 | ||

11.7 Entering the data | 132 | ||

11.8 Related t-test | 133 | ||

11.9 Interpreting the output | 133 | ||

Summary of SPSS steps for related t-test | 135 | ||

12 Unrelated t-test: Comparing two groups of unrelated/uncorrelated scores | 136 | ||

Overview | 136 | ||

12.1 What is the unrelated t-test? | 137 | ||

12.2 When to use the unrelated t-test | 138 | ||

12.3 When not to use the unrelated t-test | 138 | ||

12.4 Data requirements for the unrelated t-test | 139 | ||

12.5 Problems in the use of the unrelated t-test | 139 | ||

12.6 Data to be analysed | 139 | ||

12.7 Entering the data | 139 | ||

12.8 Unrelated t-test | 141 | ||

12.9 Interpreting the output | 141 | ||

Summary of SPSS steps for unrelated t-test | 143 | ||

13 Confidence intervals | 144 | ||

Overview | 144 | ||

13.1 What are confidence intervals? | 145 | ||

13.2 Relationship between significance and confidence intervals | 146 | ||

13.3 Confidence intervals and limits in SPSS | 147 | ||

14 Chi-square: Differences between unrelated samples of frequency data | 148 | ||

Overview | 148 | ||

14.1 What is chi-square? | 149 | ||

14.2 When to use chi-square | 151 | ||

14.3 When not to use chi-square | 151 | ||

14.4 Data requirements for chi-square | 152 | ||

14.5 Problems in the use of chi-square | 152 | ||

14.6 Data to be analysed | 153 | ||

14.7 Entering the data using the â€˜Weighting Casesâ€™ procedure | 153 | ||

14.8 Entering the data case by case | 154 | ||

14.9 Chi-square | 155 | ||

14.10 Interpreting the output for chi-square | 156 | ||

14.11 Fisherâ€™s exact test | 158 | ||

14.12 Interpreting the output for Fisherâ€™s exact test | 158 | ||

14.13 One-sample chi-square | 159 | ||

14.14 Interpreting the output for a one-sample chi-square | 161 | ||

14.15 Chi-square without ready-made tables | 161 | ||

Summary of SPSS steps for chi-square | 162 | ||

15 McNemarâ€™s test: Differences between related samples of frequency data | 163 | ||

Overview | 163 | ||

15.1 What is McNemarâ€™s test? | 164 | ||

15.2 When to use McNemarâ€™s test | 164 | ||

15.3 When not to use McNemarâ€™s test | 165 | ||

15.4 Data requirements for McNemarâ€™s test | 165 | ||

15.5 Problems in the use of McNemarâ€™s test | 165 | ||

15.6 Data to be analysed | 165 | ||

15.7 Entering the data using the â€˜Weighting Casesâ€™ procedure | 166 | ||

15.8 Entering the data case by case | 167 | ||

15.9 McNemarâ€™s test | 167 | ||

15.10 Interpreting the output for McNemarâ€™s test | 168 | ||

Summary of SPSS steps for McNemarâ€™s test | 169 | ||

16 Ranking tests for two groups: Non-parametric statistics | 170 | ||

Overview | 170 | ||

16.1 What are non-parametric tests? | 171 | ||

16.2 When to use non-parametric tests | 173 | ||

16.3 When not to use non-parametric tests | 173 | ||

16.4 Data requirements for non-parametric tests | 173 | ||

16.5 Problems in the use of non-parametric tests | 173 | ||

16.6 Data to be analysed | 174 | ||

16.7 Entering the data | 174 | ||

16.8 Related scores: Sign test | 175 | ||

16.9 Interpreting the output for the sign test | 175 | ||

16.10 Related scores: Wilcoxon test | 176 | ||

16.11 Interpreting the output for the Wilcoxon test | 176 | ||

16.12 Unrelated scores: Mannâ€“Whitney U-test | 177 | ||

16.13 Entering the data | 177 | ||

16.14 Mannâ€“Whitney U-test | 178 | ||

16.15 Interpreting the output for the Mannâ€“Whitney U-test | 179 | ||

Summary of SPSS steps for non-parametric tests for two groups | 180 | ||

17 Ranking tests for three or more groups: Non-parametric statistics | 181 | ||

Overview | 181 | ||

17.1 What are ranking tests? | 182 | ||

17.2 When to use ranking tests | 183 | ||

17.3 When not to use ranking tests | 183 | ||

17.4 Data requirements for ranking tests | 183 | ||

17.5 Problems in the use of ranking tests | 183 | ||

17.6 Data to be analysed | 183 | ||

17.7 Friedman three or more related samples test | 184 | ||

17.8 Entering the data for the Friedman test | 184 | ||

17.9 Friedman test | 185 | ||

17.10 Interpreting the output for the Friedman test | 185 | ||

17.11 Kruskalâ€“Wallis three or more unrelated samples test | 186 | ||

17.12 Entering the data for the Kruskalâ€“Wallis test | 187 | ||

17.13 Kruskalâ€“Wallis test | 188 | ||

17.14 Interpreting the output for the Kruskalâ€“Wallis test | 189 | ||

Summary of SPSS steps for non-parametric tests for three or more groups | 189 | ||

Part 4 Analysis of variance | 191 | ||

18 One-way analysis of variance (ANOVA) for unrelated or uncorrelated scores | 193 | ||

Overview | 193 | ||

18.1 What is one-way unrelated ANOVA? | 194 | ||

18.2 When to use one-way unrelated ANOVA | 195 | ||

18.3 When not to use one-way unrelated ANOVA | 196 | ||

18.4 Data requirements for one-way unrelated ANOVA | 196 | ||

18.5 Problems in the use of one-way unrelated ANOVA | 196 | ||

18.6 Data to be analysed | 196 | ||

18.7 Entering the data | 197 | ||

18.8 One-way unrelated ANOVA | 197 | ||

18.9 Interpreting the output | 198 | ||

Summary of SPSS steps for one-way unrelated ANOVA | 199 | ||

19 One-way analysis of variance for correlated scores or repeated measures | 201 | ||

Overview | 201 | ||

19.1 What is one-way repeated-measures ANOVA? | 202 | ||

19.2 When to use repeated-measures ANOVA | 203 | ||

19.3 When not to use one-way repeated-measures ANOVA | 203 | ||

19.4 Data requirements for one-way repeated-measures ANOVA | 204 | ||

19.5 Problems in the use of one-way repeated-measures ANOVA | 204 | ||

19.6 Data to be analysed | 204 | ||

19.7 Entering the data | 204 | ||

19.8 One-way repeated-measures ANOVA | 205 | ||

19.9 Interpreting the output | 207 | ||

Summary of SPSS steps for one-way repeated-measures ANOVA | 209 | ||

20 Two-way analysis of variance for unrelated/uncorrelated scores | 210 | ||

Overview | 210 | ||

20.1 What is two-way unrelated ANOVA? | 211 | ||

20.2 When to use two-way unrelated ANOVA | 214 | ||

20.3 When not to use two-way unrelated ANOVA | 214 | ||

20.4 Data requirements for two-way unrelated ANOVA | 214 | ||

20.5 Problems in the use of two-way unrelated ANOVA | 215 | ||

20.6 Data to be analysed | 216 | ||

20.7 Entering the data | 216 | ||

20.8 Two-way unrelated ANOVA | 217 | ||

20.9 Interpreting the output | 218 | ||

20.10 Editing the graph | 220 | ||

Summary of SPSS steps for two-way unrelated ANOVA | 221 | ||

21 Multiple comparisons in ANOVA | 223 | ||

Overview | 223 | ||

21.1 What is multiple-comparisons testing? | 224 | ||

21.2 When to use multiple-comparisons tests | 225 | ||

21.3 When not to use multiple-comparisons tests | 225 | ||

21.4 Data requirements for multiple-comparisons tests | 225 | ||

21.5 Problems in the use of multiple-comparisons tests | 226 | ||

21.6 Data to be analysed | 226 | ||

21.7 Entering the data | 227 | ||

21.8 Multiple-comparisons tests | 227 | ||

21.9 Interpreting the output | 228 | ||

21.10 Reporting the output | 229 | ||

Summary of SPSS steps for multiple-comparison tests | 230 | ||

22 Two-way analysis of variance for correlated scores or repeated measures | 231 | ||

Overview | 231 | ||

22.1 What is two-way repeated-measures ANOVA? | 232 | ||

22.2 When to use two-way repeated-measures ANOVA | 234 | ||

22.3 When not to use two-way repeated-measures ANOVA | 235 | ||

22.4 Data requirements for two-way related-measures ANOVA | 235 | ||

22.5 Problems in the use of two-way repeated-measures ANOVA | 235 | ||

22.6 Data to be analysed | 235 | ||

22.7 Entering the data | 236 | ||

22.8 Two-way repeated-measures ANOVA | 236 | ||

22.9 Interpreting the output | 238 | ||

22.10 Reporting the output | 242 | ||

Summary of SPSS steps for two-way repeated-measures ANOVA | 242 | ||

23 Two-way mixed analysis of variance | 244 | ||

Overview | 244 | ||

23.1 What is two-way mixed ANOVA? | 245 | ||

23.2 When to use two-way mixed ANOVA | 245 | ||

23.3 When not to use two-way mixed ANOVA | 246 | ||

23.4 Data requirements for two-way mixed ANOVA | 247 | ||

23.5 Problems in the use of two-way mixed ANOVA | 247 | ||

23.6 Data to be analysed | 247 | ||

23.7 Entering the data | 247 | ||

23.8 Two-way mixed ANOVA | 248 | ||

23.9 Interpreting the output | 250 | ||

23.10 Reporting the output | 251 | ||

Summary of SPSS steps for mixed ANOVA | 252 | ||

24 One-way analysis of covariance (ANCOVA) | 254 | ||

Overview | 254 | ||

24.1 What is one-way analysis of covariance (ANCOVA)? | 255 | ||

24.2 When to use one-way ANCOVA | 256 | ||

24.3 When not to use one-way ANCOVA | 256 | ||

24.4 Data requirements for one-way ANCOVA | 257 | ||

24.5 Problems in the use of one-way ANCOVA | 257 | ||

24.6 Data to be analysed | 257 | ||

24.7 Entering the data | 257 | ||

24.8 One-way ANCOVA | 258 | ||

24.9 Testing that the slope of the regression line within cells is similar | 259 | ||

24.10 Interpreting the output | 260 | ||

24.11 Testing the full model | 260 | ||

24.12 Interpreting the output | 262 | ||

24.13 Reporting the output | 263 | ||

Summary of SPSS steps for one-way ANCOVA | 263 | ||

25 One-way multivariate analysis of variance (MANOVA) | 265 | ||

Overview | 265 | ||

25.1 What is one-way multivariate analysis of variance (MANOVA)? | 266 | ||

25.2 When to use one-way MANOVA | 267 | ||

25.3 When not to use one-way MANOVA | 268 | ||

25.4 Data requirements for one-way MANOVA | 269 | ||

25.5 Problems in the use of one-way MANOVA | 269 | ||

25.6 Data to be analysed | 269 | ||

25.7 Entering the data | 270 | ||

25.8 One-way MANOVA | 270 | ||

25.9 Interpreting the output | 271 | ||

25.10 Reporting the output | 274 | ||

Summary of SPSS steps for one-way MANOVA | 274 | ||

Part 5 More advanced statistics | 275 | ||

26 Partial correlation | 277 | ||

Overview | 277 | ||

26.1 What is partial correlation? | 278 | ||

26.2 When to use partial correlation | 280 | ||

26.3 When not to use partial correlation | 280 | ||

26.4 Data requirements for partial correlation | 280 | ||

26.5 Problems in the use of partial correlation | 280 | ||

26.6 Data to be analysed | 280 | ||

26.7 Entering the data | 281 | ||

26.8 Partial correlation | 281 | ||

26.9 Interpreting the output | 282 | ||

Reporting the output | 283 | ||

Summary of SPSS steps for partial correlation | 283 | ||

27 Factor analysis | 284 | ||

Overview | 284 | ||

27.1 What is factor analysis? | 285 | ||

27.2 When to use factor analysis | 287 | ||

27.3 When not to use factor analysis | 288 | ||

27.4 Data requirements for factor analysis | 288 | ||

27.5 Problems in the use of factor analysis | 288 | ||

27.6 Data to be analysed | 289 | ||

27.7 Entering the data | 289 | ||

27.8 Principal components analysis with orthogonal rotation | 290 | ||

27.9 Interpreting the output | 293 | ||

27.10 Reporting the output | 295 | ||

Summary of SPSS steps for factor analysis | 296 | ||

28 Item reliability and inter-rater agreement | 297 | ||

Overview | 297 | ||

28.1 What are item reliability and inter-rater agreement? | 298 | ||

28.2 When to use item reliability and inter-rater agreement | 300 | ||

28.3 When not to use item reliability and inter-rater agreement | 301 | ||

28.4 Data requirements for item reliability and inter-rater agreement | 301 | ||

28.5 Problems in the use of item reliability and inter-rater agreement? | 302 | ||

28.6 Data to be analysed for item alpha reliability | 302 | ||

28.7 Entering the data | 302 | ||

28.8 Alpha reliability | 303 | ||

28.9 Interpreting the output | 304 | ||

28.10 Split-half reliability | 305 | ||

28.11 Interpreting the output | 305 | ||

28.12 Data to be analysed for inter-rater agreement (kappa) | 306 | ||

28.13 Entering the data | 306 | ||

28.14 Kappa | 307 | ||

28.15 Interpreting the output | 308 | ||

Summary of SPSS steps for reliability | 309 | ||

29 Stepwise multiple regression | 310 | ||

Overview | 310 | ||

29.1 What is stepwise multiple regression? | 311 | ||

29.2 When to use stepwise multiple regression | 312 | ||

29.3 When not to use stepwise multiple regression | 313 | ||

29.4 Data requirements for stepwise multiple regression | 314 | ||

29.5 Problems in the use of stepwise multiple regression | 314 | ||

29.6 Data to be analysed | 314 | ||

29.7 Entering the data | 315 | ||

29.8 Stepwise multiple regression analysis | 315 | ||

29.9 Interpreting the output | 316 | ||

29.10 Reporting the output | 319 | ||

Summary of SPSS steps for stepwise multiple regression | 319 | ||

30 Simultaneous or standard multiple regression | 321 | ||

Overview | 321 | ||

30.1 What is simultaneous or standard multiple regression? | 322 | ||

30.2 When to use simultaneous or standard multiple regression | 325 | ||

30.3 When not to use simultaneous or standard multiple regression | 326 | ||

30.4 Data requirements for simultaneous or standard multiple regression | 326 | ||

30.5 Problems in the use of simultaneous or standard multiple regression | 327 | ||

30.6 Data to be analysed | 327 | ||

30.7 Entering the data | 327 | ||

30.8 Simultaneous or standard multiple regression analysis | 328 | ||

30.9 Interpreting the output | 329 | ||

30.10 Reporting the output | 331 | ||

Summary of SPSS steps for simultaneous or standard multiple regression | 333 | ||

31 Simple mediational analysis | 334 | ||

Overview | 334 | ||

31.1 What is simple mediational analysis? | 335 | ||

31.2 When to use simple mediational analysis | 338 | ||

31.3 When not to use simple mediational analysis | 338 | ||

31.4 Data requirements for a simple mediational analysis | 339 | ||

31.5 Problems in the use of simple mediational analysis | 339 | ||

31.6 Data to be analysed | 339 | ||

31.7 Entering the data | 339 | ||

31.8 Simultaneous multiple regression analysis | 340 | ||

31.9 Interpreting the output | 341 | ||

31.10 Reporting the output | 342 | ||

Summary of SPSS steps for simultaneous or standard multiple regression | 343 | ||

32 Hierarchical multiple regression | 344 | ||

Overview | 344 | ||

32.1 What is hierarchical multiple regression? | 345 | ||

32.2 When to use hierarchical multiple regression | 347 | ||

32.3 When not to use hierarchical multiple regression | 347 | ||

32.4 Data requirements for hierarchical multiple regression | 347 | ||

32.5 Problems in the use of hierarchical multiple regression | 347 | ||

32.6 Data to be analysed | 348 | ||

32.7 Entering the data | 348 | ||

32.8 Hierarchical multiple regression analysis | 349 | ||

32.9 Interpreting the output | 350 | ||

32.10 Reporting the output | 352 | ||

Summary of SPSS steps for hierarchical multiple regression | 353 | ||

33 Log-linear analysis | 354 | ||

Overview | 354 | ||

33.1 What is log-linear analysis? | 355 | ||

33.2 When to use log-linear analysis | 356 | ||

33.3 When not to use log-linear analysis | 357 | ||

33.4 Data requirements for log-linear analysis | 358 | ||

33.5 Problems in the use of log-linear analysis | 358 | ||

33.6 Data to be analysed | 358 | ||

33.7 Entering the data | 358 | ||

33.8 Log-linear analysis | 359 | ||

33.9 Interpreting the output | 360 | ||

33.10 Reporting the output | 362 | ||

Summary of SPSS steps for log-linear analysis | 362 | ||

34 Meta-analysis | 363 | ||

Overview | 363 | ||

34.1 What is meta-analysis? | 364 | ||

34.2 When to use meta-analysis | 367 | ||

34.3 When not to use meta-analysis | 368 | ||

34.4 Data requirements for meta-analysis | 368 | ||

34.5 Problems in the use of meta-analysis | 369 | ||

34.6 Data to be analysed | 369 | ||

34.7 Meta-analysis | 369 | ||

34.8 Interpreting the output | 371 | ||

34.9 Reporting the output | 371 | ||

Part 6 Data handling procedures | 373 | ||

35 Missing values | 375 | ||

Overview | 375 | ||

35.1 What are missing values? | 376 | ||

35.2 Entering the data | 377 | ||

35.3 Defining missing values | 378 | ||

35.4 Pairwise and listwise options | 378 | ||

35.5 Sample output for pairwise exclusion | 379 | ||

35.6 Sample output for listwise exclusion | 380 | ||

35.7 Interpreting the output | 380 | ||

35.8 Reporting the output | 381 | ||

Summary of SPSS steps for handling missing values | 381 | ||

36 Recoding values | 382 | ||

Overview | 382 | ||

36.1 What is recoding values? | 383 | ||

36.2 Entering the data | 383 | ||

36.3 Recoding values | 384 | ||

36.4 Recoding missing values | 387 | ||

36.5 Saving the recode procedure as a syntax file | 387 | ||

36.6 Adding some extra cases to Table 36.1 | 388 | ||

36.7 Running the Recode syntax command | 388 | ||

Summary of SPSS steps for recoding values | 388 | ||

37 Computing a scale score with some values missing | 390 | ||

Overview | 390 | ||

37.1 What is computing a scale score with some values missing? | 391 | ||

37.2 Entering the data | 392 | ||

37.3 Computing a scale score with some values missing | 393 | ||

37.4 Saving the Compute procedure as a syntax file | 395 | ||

37.5 Adding some extra cases to Table 37.1 | 395 | ||

37.6 Running the Compute syntax command | 396 | ||

Summary of SPSS steps for computing a scale score with some missing values | 396 | ||

38 Computing a new group variable from existing group variables | 397 | ||

Overview | 397 | ||

38.1 What is computing a new group variable from existing group variables? | 398 | ||

38.2 Entering the data | 400 | ||

38.3 Syntax file for computing a new group variable from existing group variables | 400 | ||

38.4 Running the Compute syntax commands | 401 | ||

38.5 Computing a new group using menus and dialogue boxes | 402 | ||

Summary of SPSS steps for computing a new group variable from existing group variables | 403 | ||

39 Selecting cases | 404 | ||

Overview | 404 | ||

39.1 What is selecting cases? | 405 | ||

39.2 Entering the data | 406 | ||

39.3 Selecting cases | 406 | ||

Summary of SPSS steps for selecting cases | 409 | ||

40 Reading ASCII or text files into the â€˜Data Editorâ€™ | 410 | ||

Overview | 410 | ||

40.1 What is an ASCII or text data file? | 411 | ||

40.2 Entering data into an ASCII or text data file | 412 | ||

40.3 Reading an ASCII or text data file | 413 | ||

Summary of SPSS steps for inputting an ASCII or text data file | 416 | ||

Glossary | 417 | ||

Index | 424 |