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

• Includes examples from many fields of social sciences to help users understand the range of applications of statistics in data analysis
• Guidance on what kinds of data to enter and how, the SPSS steps needed to complete your analysis and how to understand and write-up the results of the analysis
• Comprehensive discussion and user-friendly guidance on the full range of statistical techniques, when it is used, when it should not be used , the sorts of data required for the analysis and common problems that cause users difficulty
• Explains step-by-step how to enter, analyse and interpret data using SPSS
• Gives detail about what to report and how to report it
• In-text features such as ‘research design issue’, ‘calculation’ and the advice boxes help structure study into manageable chunks whilst overviews and key points help with revision
• Includes a comprehensive glossary
• Full colour, bringing illustrations and explanations to life.

Your opinions count

Be the first to review this product. Write your review now.