ABSTRACT

This is a complete guide to statistics and SPSS for social science students. Statistics with SPSS for Social Science provides a step-by-step explanation of all the important statistical concepts, tests and procedures. It is also a guide to getting started with SPSS, and includes screenshots to illustrate explanations. With examples specific to social sciences, this text is essential for any student in this area.

part 1|133 pages

Descriptive statistics

chapter 1|17 pages

Why you need statistics

Types of data

chapter 2|20 pages

Describing Variables

Tables and diagrams

chapter 3|15 pages

Describing variables numerically

Averages, variation and spread

chapter 4|12 pages

Shapes of distributions of scores

chapter 5|14 pages

Standard deviation, z-scores and standard error

The standard unit of measurement in statistics

chapter 6|18 pages

Relationships between two or more variables

Diagrams and tables

chapter 7|19 pages

Correlation coefficients

The Pearson correlation and Spearman's rho

chapter 8|16 pages

Regression and standard error

part 2|62 pages

Inferential statistics

chapter 10|13 pages

The related t-test

Comparing two samples of correlated/related scores

chapter 11|18 pages

The unrelated t-test

Comparing two samples of unrelated/uncorrelated scores

chapter 12|21 pages

Chi-square

Differences between samples of frequency data

part 3|77 pages

Introduction to analysis of variance

chapter 13|13 pages

Analysis of variance (ANOVA)

Introduction to one-way unrelated or uncorrelated ANOVA

chapter 14|28 pages

Two-way analysis of variance for unrelated/uncorrelated scores

Two studies for the price of one?

chapter 15|18 pages

Analysis of covariance (ANCOVA)

Controlling for additional variables

chapter 16|16 pages

Multivariate analysis of variance (MANOVA)

part 4|131 pages

More advanced statistics and techniques

chapter 17|11 pages

Partial correlation

Spurious correlation, third or confounding variables (control variables), suppressor variables

chapter 18|20 pages

Factor analysis

Simplifying complex data

chapter 19|24 pages

Multiple regression and multiple correlation

chapter 20|25 pages

Multinomial logistic regression

Distinguishing between several different categories or groups

chapter 21|21 pages

Binomial logistic regression

chapter 22|28 pages

Log-linear methods

The analysis of complex contingency tables