Statistical Methods For The Social Sciences by Alan AgrestiStatistical Methods For The Social Sciences by Alan Agresti

Statistical Methods For The Social Sciences

byAlan Agresti

Hardcover | January 1, 2017

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Statistical methods applied to social sciences, made accessible to all through an emphasis on concepts  Statistical Methods for the Social Sciences introduces statistical methods to students majoring in social science disciplines. With an emphasis on concepts and applications, this book assumes you have no previous knowledge of statistics and only a minimal mathematical background. It contains sufficient material for a two-semester course. The 5th Edition gives you examples and exercises with a variety of “real data.” It includes more illustrations of statistical software for computations and takes advantage of the outstanding applets to explain key concepts, such as sampling distributions and conducting basic data analyses. It continues to downplay mathematics–often a stumbling block for students–while avoiding reliance on an overly simplistic recipe-based approach to statistics.

Alan Agresti is Distinguished Professor in the Department of Statistics at the University of Florida. He has been teaching statistics there for 30 years, including the development of three courses in statistical methods for social science students and three courses in categorical data analysis. He is author of over 100 refereed artic...
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Title:Statistical Methods For The Social SciencesFormat:HardcoverDimensions:608 pages, 10.25 × 8.35 × 1.55 inPublished:January 1, 2017Publisher:Pearson EducationLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:013450710X

ISBN - 13:9780134507101

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Table of Contents


  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. Model Building with Multiple Regression

  13. Logistic Regression: Modeling Categorical Responses

  14. An Introduction to Advanced Methodology