Introduction to Statistics with SPSS for Social Science

<p>This is a complete guide to statistics and SPSS for social science students. <i>Statistics with SPSS for Social Science</i> 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.</p> <p><b><i>Part One Descriptive Statistics.</i></b></p><ul> <li>Chapter 1 Why you need statistics: types of data </li> <li>Chapter 2 Describing variables: Tables and diagrams </li> <li>Chapter 3 Describing variables numerically: averages, variation and spread </li> <li>Chapter 4 Shapes of distributions of scores </li> <li>Chapter 5 - Standard deviation, z-scores and standard error: the standard unit of measurement in statistics </li> <li>Chapter 6 Relationships between two or more variables: diagrams and tables </li> <li>Chapter 7 Correlation coefficients: Pearson correlation and Spearmans rho </li> <li>Chapter 8 Regression and standard error </li> </ul><p><b><i>Part Two: Comparing Two or More Variables and the Analysis of Variance.</i></b></p><ul> <li>Chapter 9 - The analysis of a questionnaire/survey project </li> <li>Chapter 10 The related t-test: Comparing two samples of correlated/related scores </li> <li>Chapter 11 the unrelated t-test: comparing two samples of unrelated/uncorrelated scores </li> <li>Chapter 12 Chi-square: Differences between samples of frequency data </li> </ul><p><em><strong>Part Three: Introduction to Analysis of Variance</strong></em></p><ul> <li>Chapter 13 Analysis of variance (ANOVA): introduction to one-way unrelated or uncorrelated ANOVA </li> <li>Chapter 14 Two way analysis of variance for unrelated/uncorrelated scores: two studies for the price of one? </li> <li>Chapter 15 Analysis of covariance (ANCOVA): controlling for additional variables </li> <li>Chapter 16 Multivariate analysis of variance (MANOVA)</li> </ul><p><b><i>Part Four: More advanced correlational statistics and techniques</i></b></p><ul> <li>Chapter 17 - Partial correlation: spurious correlation, third or confounding variables (control variables), suppressor variables </li> <li>Chapter 18 Factor analysis: simplifying complex data </li> <li>Chapter 19 Multiple regression and multiple correlation </li> <li>Chapter 20 Multinomial logistic regression: Distinguishing between several different categories or groups </li> <li>Chapter 21 - Bionomial logistic regression </li> <li>Chapter 22 - Log-linear methods: The analysis of complex contingency tables</li> </ul>