This introductory text provides students with a conceptual understanding of basic statistical procedures, as well as the computational skills needed to complete them. The clear presentation, accessible language, and step-by-step instruction make it easy for students from a variety of social science disciplines to grasp the material. The scenarios presented in chapter exercises span the curriculum, from political science to marketing, so that students make a connection between their own area of interest and the study of statistics. Unique coverage focuses on concepts critical to understanding current statistical research such as power and sample size, multiple comparison tests, multiple regression, and analysis of covariance. Additional SPSS coverage throughout the text includes computer printouts and expanded discussion of their contents in interpreting the results of sample exercises. 1. Introduction. 2. Organizing and Graphing Data. 3. Describing Distributions: Individual Scores, Central Tendency, and Variation. 4. The Normal Distribution. 5. Correlation: A Measure of Relationship. 6. Linear Regression: Prediction. 7. Sampling, Probability, and Sampling Distributions. 8. Hypothesis Testing: One-Sample Case for the Mean. 9. Estimation: One-Sample Case for the Mean. 10. Hypothesis Testing: One-Sample Case for Other Statistics. 11. Hypothesis Testing: Two-Sample Case for the Mean. 12. Hypothesis Testing: Two-Sample Case for Other Statistics. 13. Determining Power and Sample Size. 14. Hypothesis Testing, K-Sample Case: Analysis of Variance, One-Way Classification. 15. Multiple-Comparison Procedures. 16. Analysis of Variance, Two-Way Classification. 17. Linear Regression: Estimation and Hypothesis Testing. 18. Multiple Linear Regression. 19. Analysis of Covariance. 20. Other Correlation Coefficients. 21. Chi-Square (X2) Tests for Frequencies. 22. Other Nonparametric Tests.
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