| Nota di contenuto |
Cover -- Contents -- Guided tour -- Introduction -- Acknowledgements -- Key differences between IBM SPSS Statistics 22 and earlier versions -- Part 1 Introduction to SPSS Statistics -- 1 A brief introduction to statistics -- Overview -- 1.1 Basic statistical concepts essential in SPSS Statistics analyses -- 1.2 Basic research designs: comparative versus correlational designs -- 1.3 The different types of variables in statistics -- 1.4 Descriptive and inferential statistics compared -- 1.5 Related versus unrelated designs -- 1.6 Quick summaries of statistical analyses -- 1.7 Which procedure or test to use -- 2 Basics of SPSS Statistics data entry and statistical analysis -- Overview -- 2.1 What is SPSS Statistics? -- 2.2 Accessing SPSS Statistics -- 2.3 Entering data -- 2.4 Moving within a window with the mouse -- 2.5 Moving within a window using the keyboard keys with the mouse -- 2.6 Saving data to disk -- 2.7 Opening up a data file -- 2.8 Using 'Variable View' to create and label variables -- 2.9 More on 'Data View' -- 2.10 A simple statistical calculation with SPSS -- 2.11 The SPSS Statistics output -- Summary of SPSS Statistics steps for a statistical analysis -- Part 2 Descriptive statistics -- 3 Describing variables: Tables -- Overview -- 3.1 What are tables? -- 3.2 When to use tables -- 3.3 When not to use tables -- 3.4 Data requirements for tables -- 3.5 Problems in the use of tables -- 3.6 The data to be analysed -- 3.7 Entering summarised categorical or frequency data by weighting -- 3.8 Percentage frequencies -- 3.9 Interpreting the output -- REPORTING THE OUTPUT -- Summary of SPSS Statistics steps for frequency tables -- 4 Describing variables: Diagrams -- Overview -- 4.1 What are diagrams? -- 4.2 When to use diagrams -- 4.3 When not to use diagrams -- 4.4 Data requirements for diagrams -- 4.5 Problems in the use of diagrams.
4.6 The data to be analysed -- 4.7 Entering summarised categorical or frequency data by weighting -- 4.8 Pie diagram of category data -- 4.9 Adding labels to the pie diagram and removing the legend and label -- 4.10 Changing the colour of a pie diagram slice to a black and white pattern -- 4.11 Bar chart of category data -- 4.12 Histograms -- Summary of SPSS steps for charts -- 5 Describing variables numerically: Averages, variation and spread -- Overview -- 5.1 What are averages, variation and spread? -- 5.2 When to use averages, variation and spread -- 5.3 When not to use averages, variation and spread -- 5.4 Data requirements for averages, variation and spread -- 5.5 Problems in the use of averages, variation and spread -- 5.6 The data to be analysed -- 5.7 Entering the data -- 5.8 Mean, median, mode, standard deviation, variance and range -- 5.9 Interpreting the output -- 5.10 Other features -- REPORTING THE OUTPUT -- Summary of SPSS Statistics steps for descriptive statistics -- 6 Shapes of distributions of scores -- Overview -- 6.1 What are the different shapes of scores? -- 6.2 When to use histograms and frequency tables of scores -- 6.3 When not to use histograms and frequency tables of scores -- 6.4 Data requirements for using histograms and frequency tables of scores -- 6.5 Problems in using histograms and frequency tables of scores -- 6.6 The data to be analysed -- 6.7 Entering the data -- 6.8 Frequency tables -- 6.9 Interpreting the output -- REPORTING THE OUTPUT -- 6.10 Histograms -- 6.11 Interpreting the output -- REPORTING THE OUTPUT -- Summary of SPSS Statistics steps for frequency distributions -- 7 Standard deviation: The standard unit of measurement in statistics -- Overview -- 7.1 What is standard deviation? -- 7.2 When to use standard deviation -- 7.3 When not to use standard deviation.
7.4 Data requirements for standard deviation -- 7.5 Problems in the use of standard deviation -- 7.6 The data to be analysed -- 7.7 Entering the data -- 7.8 Standard deviation -- 7.9 Interpreting the output -- 7.10 Z -scores -- 7.11 Other features -- REPORTING THE OUTPUT -- Summary of SPSS Statistics steps for standard deviation -- 8 Relationships between two or more variables: Tables -- Overview -- 8.1 What tables are used to show relationships between variables? -- 8.2 When to use tables to show relationships between variables -- 8.3 When not to use tables to show relationships between variables -- 8.4 Data requirements for tables to show relationships between variables -- 8.5 Problems in the use of tables to show relationships between variables -- 8.6 The data to be analysed -- 8.7 Entering the data -- 8.8 Weighting the data -- 8.9 Cross-tabulation with frequencies -- 8.10 Displaying frequencies as a percentage of the total number -- 8.11 Displaying frequencies as a percentage of the column total -- Summary of SPSS Statistics steps for contingency tables -- 9 Relationships between two or more variables: Diagrams -- Overview -- 9.1 What diagrams are used to show relationships between variables? -- 9.2 When to use diagrams to show relationships between variables -- 9.3 When not to use diagrams to show relationships between variables -- 9.4 Data requirements for diagrams to show relationships between variables -- 9.5 Problems in the use of diagrams to show relationships between variables -- 9.6 The data to be analysed -- 9.7 Entering the data -- 9.8 Weighting the data -- 9.9 Compound (stacked) percentage bar chart -- 9.10 Compound (clustered) bar chart -- Summary of SPSS Statistics steps for bar charts -- 10 Correlation coefficients: Pearson's correlation and Spearman's rho -- Overview -- 10.1 What is a correlation coefficient?.
10.2 When to use Pearson and Spearman rho correlation coefficients -- 10.3 When not to use Pearson and Spearman rho correlation coefficients -- 10.4 Data requirements for Pearson and Spearman rho correlation coefficients -- 10.5 Problems in the use of correlation coefficients -- 10.6 The data to be analysed -- 10.7 Entering the data -- 10.8 Pearson's correlation -- 10.9 Interpreting the output -- REPORTING THE OUTPUT -- 10.10 Spearman's rho -- 10.11 Interpreting the output -- REPORTING THE OUTPUT -- 10.12 Scatter diagram -- 10.13 Interpreting the output -- REPORTING THE OUTPUT -- 10.14 Scattergram with more than one case with the same two values -- Summary of SPSS Statistics steps for correlation -- 11 Regression: Prediction with precision -- Overview -- 11.1 What is simple regression? -- 11.2 When to use simple regression -- 11.3 When not to use simple regression -- 11.4 Data requirements for simple regression -- 11.5 Problems in the use of simple regression -- 11.6 The data to be analysed -- 11.7 Entering the data -- 11.8 Simple regression -- 11.9 Interpreting the output -- 11.10 Regression scatterplot -- 11.11 Interpreting the output -- REPORTING THE OUTPUT -- Summary of SPSS Statistics steps for simple regression -- Part 3 Significance testing and basic inferential tests -- 12 Standard error -- Overview -- 12.1 What is standard error? -- 12.2 When to use standard error -- 12.3 When not to use standard error -- 12.4 Data requirements for standard error -- 12.5 Problems in the use of standard error -- 12.6 The data to be analysed -- 12.7 Entering the data -- 12.8 Estimated standard error of the mean -- 12.9 Interpreting the output -- REPORTING THE OUTPUT -- Summary of SPSS Statistics steps for standard error -- 13 The t-test: Comparing two samples of correlated/related/paired scores -- Overview -- 13.1 What is the related t-test?.
13.2 When to use the related t-test -- 13.3 When not to use the related t-test -- 13.4 Data requirements for the related t-test -- 13.5 Problems in the use of the related t-test -- 13.6 The data to be analysed -- 13.7 Entering the data -- 13.8 Related t-test -- 13.9 Interpreting the output -- REPORTING THE OUTPUT -- Summary of SPSS Statistics steps for related t-test -- 14 The t-test: Comparing two groups of unrelated/uncorrelated scores -- Overview -- 14.1 What is the unrelated t-test? -- 14.2 When to use the unrelated t-test -- 14.3 When not to use the unrelated t-test -- 14.4 Data requirements for the unrelated t-test -- 14.5 Problems in the use of the unrelated t-test -- 14.6 The data to be analysed -- 14.7 Entering the data -- 14.8 Unrelated t-test -- 14.9 Interpreting the output -- REPORTING THE RESULTS -- Summary of SPSS Statistics steps for unrelated t -test -- 15 Confidence intervals -- Overview -- 15.1 What are confidence intervals? -- 15.2 The relationship between significance and confidence intervals -- 15.3 Confidence intervals and limits in SPSS Statistics -- 16 Chi-square: Differences between unrelated samples of frequency data -- Overview -- 16.1 What is chi-square? -- 16.2 When to use chi-square -- 16.3 When not to use chi-square -- 16.4 Data requirements for chi-square -- 16.5 Problems in the use of chi-square -- 16.6 The data to be analysed -- 16.7 Entering the data using the 'Weighting Cases' procedure -- 16.8 Entering the data case by case -- 16.9 Chi-square -- 16.10 Interpreting the output for chi-square -- REPORTING THE OUTPUT -- 16.11 Fisher's exact test -- 16.12 Interpreting the output for Fisher's exact test -- REPORTING THE OUTPUT -- 16.13 One-sample chi-square -- 16.14 Interpreting the output for a one-sample chi-square -- REPORTING THE OUTPUT -- 16.15 Chi-square without ready-made tables.
Summary of SPSS Statistics steps for chi-square.
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Everyday Life and the Unconscious Mind : An Introduction to Psychoanalytic Concepts / / by Hannah Curtis
