Statistics

For an introductory course in statistics for undergraduate or graduate students in departments of sociology, political science, and psychology, geography, anthropology, journalism, and speech.

Assuming no prior knowledge of statistics, these authors combine their varied backgrounds—one a statistician, the other a social scientist—to introduce statistical methods with a high degree of statistical accuracy and a wealth of examples that are interesting and relevant to social scientists. The Third Edition has been both updated and improved to integrate real-world data into examples and exercises and make coverage more accessible throughout the text.

• Provides coverage that is technically accurate yet presented with an accessible, non-technical approach.

• Downplays the use of formulaic calculations, emphasizing concepts, interpretations and the use of computer software for conducting analyses.

• Splits coverage into introductory and more advanced material, offering enough coverage for both undergraduate- and graduate-level courses.

• Reflects the latest topics in the field, including coverage of many new methods rarely treated in other texts, such as...

  • Residuals and odds ratios for contingency tables (Ch. 8).

  • Regression diagnostics (Ch. 14).

  • Logistic regression and ordinal regression (Ch. 15).

• De-emphasizes probability—a stumbling block for many students—to concentrate on data analyses that students will see as relevant for social scientists.

• Integrates statistical inference early in the text to emphasize the interrelationship between the descriptive and inferential components of statistics.

• Emphasizes estimation methods as well as hypothesis testing for statistical inference.

• Reinforces and challenges newly acquired skills through worked examples and over 600 real data based problems.

• Introduces modern ways of analyzing data—such as following up a chi-squared test with a residual analysis and describing association using odds ratios (Ch. 8).

• Includes new material on repeated measurement analyses through a mixed model in the ANOVA chapter 12.

• Chapter 14 includes a discussion of regression diagnostics and concludes with an introduction to generalized linear models.

• Expanded coverage of logistic regression, including a discussion of a generalized logit model for ordinal data—a topic not yet explored in other texts (Ch. 15).

• Repositions coverage of model building to provide an earlier presentation of analysis of variance.

• Greater emphasis on using statistical software in place of manual computations.

• Offers more frequent, thorough examples and a stronger emphasis on applications and “real data” in both examples and problems.

• Total number of problems increased by 25%, providing many new data analysis problems.

• NEW—Introduces modern ways of analyzing data—such as following up a chi-squared test with a residual analysis and describing association using odds ratios (Ch. 8).
• NEW—Includes new material on repeated measurement analyses through a mixed model in the ANOVA chapter 12.
• NEW—Chapter 14 includes a discussion of regression diagnostics and concludes with an introduction to generalized linear models.
• NEW—Expanded coverage of logistic regression, including a discussion of a generalized logit model for ordinal data—a topic not yet explored in other texts (Ch. 15).
• NEW—Repositions coverage of model building to provide an earlier presentation of analysis of variance.
• NEW—Greater emphasis on using statistical software in place of manual computations.
• NEW—Offers more frequent, thorough examples and a stronger emphasis on applications and “real data” in both examples and problems.
• NEW—Total number of problems increased by 25%, providing many new data analysis problems.

 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. Comparing Groups: Analysis of Variance Methods.


13. Combining Regression and ANOVA: Analysis of Covariance.


14. Model Building with Multiple Regression.


15. Logistic Regression: Modeling Categorical Responses.


16. Introduction to Advanced Topics.


Appendix: SAS and SPSS for Statistical Analyses.


Tables.


Answers to Selected Problems.


Index.

Statistical Methods for the Social Sciences  (Statistics)

• 
  Statistical Methods for the Social Sciences, 4/E
  Agresti & Finlay
  ©2009 | Prentice Hall | Cloth; 624 pp | Instock
  ISBN-10: 0130272957 | ISBN-13: 9780130272959
  Brief Description | Buy from myPearsonStore

  

  The book presents an introduction to statistical methods for students majoring in social science disciplines.  No previous knowledge of statistics is assumed, and mathematical background is assumed to be minimal (lowest-level high-school algebra).

   

  The book contains sufficient material for a two-semester sequence of courses.  Such sequences are commonly required of social science graduate students in sociology, political science, and psychology. Students in geography, anthropology, journalism, and speech also are sometimes required to take at least one statistics course.
  
  Datasets and other resources (where applicable) for this book are available here.
  

• 
  Statistical Methods for the Social Sciences (Book Alone), 4/E
  Agresti & Finlay
  ©2009 | Prentice Hall | Cloth; 624 pp | Out of Stock
  ISBN-10: 0205646417 | ISBN-13: 9780205646418
  Brief Description

  

  Agresti and Finley present statistical methods in a style that emphasizes their concepts and their application to the social sciences rather than the mathematics and computational details behind them.

   

  Statistical Methods for the Social Sciences, 4e presents an introduction to statistical methods for students majoring in social science disciplines.  No previous knowledge of statistics is assumed, and mathematical background is assumed to be minimal (lowest-level high-school algebra).

   

  This text may be used in a one or two course sequence. Such sequences are commonly required of social science graduate students in sociology, political science, and psychology. Students in geography, anthropology, journalism, and speech also are sometimes required to take at least one statistics course.

• 
  Statistical Methods for the Social Sciences (with SPSS from A to Z: A Brief Step-by-Step Manual), 4/E
  Agresti & Finlay
  ©2009 | Prentice Hall | Kit/Package/ShrinkWrap; 624 pp | Instock
  ISBN-10: 0205632491 | ISBN-13: 9780205632497
  Brief Description | Buy from myPearsonStore

  

  Agresti and Finley present statistical methods in a style that emphasizes their concepts and their application to the social sciences rather than the mathematics and computational details behind them.

   

  Statistical Methods for the Social Sciences, 4e presents an introduction to statistical methods for students majoring in social science disciplines.  No previous knowledge of statistics is assumed, and mathematical background is assumed to be minimal (lowest-level high-school algebra).

   

  This text may be used in a one or two course sequence. Such sequences are commonly required of social science graduate students in sociology, political science, and psychology. Students in geography, anthropology, journalism, and speech also are sometimes required to take at least one statistics course.

Interwrite Personal Response System
EduCue, Addison-Wesley & Benjamin Cummings
©2004 | Prentice Hall | Electronic Supplement | Instock
ISBN-10: 0321267354 | ISBN-13: 9780321267351

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