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 Spearmans 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