Introduction to Statistics with SPSS for Social Science

Part One Descriptive Statistics. * Chapter 1 Why you need statistics: types of data * Chapter 2 Describing variables: Tables and diagrams * Chapter 3 Describing variables numerically: averages, variation and spread * Chapter 4 Shapes of distributions of scores * Chapter 5 - Standard deviation, z-scores and standard error: the standard unit of measurement in statistics * Chapter 6 Relationships between two or more variables: diagrams and tables * Chapter 7 Correlation coefficients: Pearson correlation and Spearman's rho * Chapter 8 Regression and standard error Part Two: Comparing Two or More Variables and the Analysis of Variance. * Chapter 9 - The analysis of a questionnaire/survey project * Chapter 10 The related t-test: Comparing two samples of correlated/related scores * Chapter 11 the unrelated t-test: comparing two samples of unrelated/uncorrelated scores * Chapter 12 Chi-square: Differences between samples of frequency data Part Three: Introduction to Analysis of Variance * Chapter 13 Analysis of variance (ANOVA): introduction to one-way unrelated or uncorrelated ANOVA * Chapter 14 Two way analysis of variance for unrelated/uncorrelated scores: two studies for the price of one? * Chapter 15 Analysis of covariance (ANCOVA): controlling for additional variables * Chapter 16 Multivariate analysis of variance (MANOVA) Part Four: More advanced correlational statistics and techniques * Chapter 17 - Partial correlation: spurious correlation, third or confounding variables (control variables), suppressor variables * Chapter 18 Factor analysis: simplifying complex data * Chapter 19 Multiple regression and multiple correlation * Chapter 20 Multinomial logistic regression: Distinguishing between several different categories or groups * Chapter 21 - Bionomial logistic regression * Chapter 22 - Log-linear methods: The analysis of complex contingency tables