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 VarianceChapter 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 techniquesChapter 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

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