: Statistical Methods for the Social Sciences (4th Edition) ( ) by Alan Agresti; Barbara Finlay and a great selection of similar New. Statistical Methods for the Social Sciences (4th Edition) by Alan Agresti, Barbara Finlay. Note: Cover may not represent actual copy or condition available. Statistical methods for the social sciences. by Alan Agresti; Barbara Finlay. Print book. English. 4th ed. Upper Saddle River, N.J.: Pearson Prentice Hall.

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Statistical methods for the social sciences. Home About Help Search. Chapter 16 includes new sections on longitudinal data analysis and multilevel hierarchical models.

Advanced topics such as regression and ANOVA emphasize interpreting output from computer packages rather than complex computing formulas. Such sequences are commonly required of social science graduate students in sociology, political abd, and psychology.

The book helps in this Showing all editions for ‘Statistical methods for the social sciences’. The fourth edition has an even stronger emphasis on concepts and applications, with greater attention to “real data” both in the examples and exercises. It has met those expectations The mathematics is still downplayed, in finnlay probability, which is all too often a stumbling block for students. The author, in this new edition, uses the symbol se for estimated standard errors, rather than the notation of sigma-hat agersti subscript having the estimator symbol.

The author is successful in his goal of editioj statistical methods in a style that emphasized their concepts and their application to the social sciences rather than the mathematics and computational details behind them.

He is author of over refereed article and four texts including “Statistics: One way analysis of variance. Language English 92 Chinese 2 Undetermined 1.

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.

Probability, sample data, and sampling distributions. The main concepts to be understood by students are sampling distribution, confidence interval, p-value, linear regression. Because of this, this book does not cover the traditional shortcut hand-computational formulas and approximations.

New to This Edition. Cancel Forgot your password? Username Password Forgot your username or password? Select All Clear All Save to: He has been teaching statistics there for 30 years, including the development of three courses in statistical methods for social science students aresti three courses in categorical data analysis. This includes some new exercises that ask students to use applets located at http: Don’t have an account?

### Statistical Methods for the Social Sciences (4th Edition) by Alan Agresti, Barbara Finlay

Remember me on this computer. A technically correct presentation. We don’t recognize your username or password. Pearson offers special pricing when you package your text with other student resources. Statistical Methods for the Social Sciences, 3rd Edition. This edition contains several changes and additions in content, directed toward ad more modern approach.

## Statistical Methods for the Social Sciences, 4th Edition

Your Web browser is not enabled for JavaScript. The author uses capital Y only as notation filay a variable and lower-case for observed values and sample statistics; thus, y-bar, rather than Y-bar, which is consistent with the lower-case used throughout for the standard deviation and other statistics. To help with this, some notation has been simplified or eliminated. Create lists, bibliographies and reviews: Students in geography, anthropology, journalism, and speech also are sometimes required to take at least one statistics course.

On the other hand, the text is not a cookbook. Emphasis on concepts, rather than computing formulas. By “modern”, I mean that it is model rather than test oriented, that it gives heavy emphasis to confidence intervals and p-values rather than using arbitrary levels of significance, and that it eschews computational formulae. The presentation of computationally complex methods, such as regression, emphasizes interpretation of software output rather than the formulas for snd the analysis.

You have successfully signed out and will be required to sign back in should you editio to download more resources. Description The book presents an introduction to statistical methods for ahd majoring in social science disciplines. Statistical methods for the social sciences by Alan Agresti; Barbara Finlay. Privacy Policy Terms and Conditions.