Statistical Methods for the Social Sciences, Global Edition

Help your students gain statistics skills for the social sciences with this accessible text Statistical Methods for the Social Sciences introduces your students to the subject in a low-technical way with no statistics knowledge necessary. This edition presents the latest information in a way ideal for two-semester courses in social science.

Statistical Methods for the Social Sciences, 5th Edition,
Global Edition, by Alan Agresti, introduces you to statistical methods used in social science disciplines with no previous knowledge of statistics necessary. With an emphasis on concepts and applications, the book requires only a minimal mathematical background, maintaining a low technical level throughout to make it accessible to beginners.

The 5th edition has a strong focus on real examples to help you learn the fundamental concepts of sampling distributions, confidence intervals, and significance tests. This approach also helps you understand how to apply your learning to the real world. This edition also emphasises the interpretation of software output rather than the formulas for performing analysis, reflecting advances in statistical software - which are more frequently used by social scientists to analyse data today.

• Numerous homework exercises
  included in each chapter.
  
• Updated data
  in most exercises.
  
• New sections
  , such as that on maximum likelihood estimation in chapter 5
  
• New examples
  ask students to use applets to help them learn the fundamental concepts of sampling distributions, confidence intervals, and significance tests.
  
• 
  The text also
  relies more on applets
  for finding tail probabilities from distributions such as the Normal, t, and chi-squared.
  

With a wide array of learning features and the latest available information, this text will equip you with the knowledge you need to succeed in your course - an ideal companion for students majoring in social science disciplines.

1. Introduction
2. Sampling and Measurement
3. Descriptive Statistics
4. Probability Distributions
5. Statistical Inference: Estimation
6. Statistical Inference: Significance Tests
7. Comparison of Two Groups
8. Analyzing Association between Categorical Variables
9. Linear Regression and Correlation
10. Introduction to Multivariate Relationships
11. Multiple Regression and Correlation
12. Regression with Categorical Predictors: Analysis of Variance Methods
13. Multiple Regression with Quantitative and Categorical Predictors
14. Model Building with Multiple Regression
15. Logistical Regression: Modeling Categorical Responses