AGRESTI FINLAY STATISTICAL METHODS FOR THE SOCIAL SCIENCES PDF

Such sequences are commonly required of social science graduate students in sociology, political Alan Agresti, Barbara Finlay The book presents an introduction to statistical methods for students majoring in social science disciplines. Statistical methods for the social sciences / Alan Agresti, Barbara Finlay Agresti, an introduction to statistical methods for students majoring in social science. Results 1 – 30 of 93 Statistical Methods for the Social Sciences by Agresti, Alan, Finlay, Barbara and a great selection of related books, art and collectibles.

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This item is rinlay of print and has been replaced with Statistical Methods for the Social Sciences, 5th Edition. 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.

It provides good examples with SPSS output.

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. It has met those expectations The main concepts to be understood by students are sampling distribution, confidence interval, p-value, linear regression.

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

Strong emphasis on regression topics. Emphasis on concepts, rather than computing formulas.

Advanced topics such as regression and ANOVA emphasize interpreting output from computer packages rather than complex computing formulas. Integration of descriptive and inferential statistics from an early point in the text. The fourth edition has an even agrestii emphasis on concepts and applications, with greater attention to “real data” both in the examples and exercises.

The mathematics is still downplayed, in particular probability, which is all too often a stumbling block for students. On the other hand, the text is not a cookbook.

Reliance on an overly simplistic recipe-based approach to statistics is not the route to good statistical practice.

Since the first edition, the increase in computer power coupled rinlay the continued improvement and accessibility of statistical software has had a major impact on the way social scientists analyze data. Because of this, this book does not cover the traditional shortcut hand-computational formulas and approximations.

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Statistical Methods for the Social Sciences, 4th Edition

The presentation of computationally complex methods, such as regression, emphasizes interpretation of software output rather than the formulas for performing the analysis.

Teh text contains numerous sample printouts, mainly in the style of SPSS and occasionaly SAS, both in chapter text and homework problems. This edition also has an appendix explaining how to apply SPSS and SAS to conduct the methods of each chapter and a website giving links to information about other software. This edition contains several changes and additions in content, directed toward a more modern approach. The main changes are as follows:. The author, in this new statiwtical, uses the symbol se for estimated standard errors, rather than the notation of sigma-hat with subscript having the estimator symbol.

Although not quite as informative, this will again make results consistent with software output, and help students connect the idea of the se for the various inferential methods they see. The author uses agresyi Y only as notation for 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.

Probability, sample data, and sampling distributions.

One way agresgi of variance. Pearson offers special pricing when you package your text with other student resources. If you’re interested in creating a cost-saving package for your students, contact your Pearson rep.

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 stayistical author of over refereed article and four texts including “Statistics: He has held visiting positions at Harvard University, Boston University, London School of Economics, and Imperial College and has taught courses or short courses for universities and companies in about 20 countries worldwide. We don’t recognize your username or password. The work is protected by local and international copyright laws and is provided solely for the use of instructors in teaching their courses and assessing student learning.

You have successfully signed out and will be required to sign back in should you need to download more resources. Statistical Methods for the Social Sciences, 4th Edition. Availability This item is out of print and has been replaced with Statistical Methods for the Social Sciences, 5th Edition.

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Description The book presents an introduction to statistical methods for students majoring in social science disciplines. 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. Reviews “This text is readable, understandable, and well-organized. Moreover, a wide variety of regression models such as linear regression, ANOVA, logistic regression are taught in the same format, essentially as special cases of a generalized linear model.

Sckences technically correct presentation. New to This Agressti. Changes in the Fourth Edition: The main changes are as follows: There is a stronger focus on real examples and on the integration of statisical software. This includes some new exercises that ask students to use applets located at http: This edition has a somewhat lower technical level in the first nine chapters, to make the book more easily accessible to undergraduate students.

To help with this, agresyi notation has been simplified or eliminated. Chapter 16 includes new sections on longitudinal data analysis and multilevel hierarchical models. Table of Contents 1. Share a link to All Resources.

Agresti & Finlay, Statistical Methods for the Social Sciences | Pearson

Websites and online courses. About the Author s. Statistical Methods for the Social Sciences, 3rd Edition. Sign In We’re sorry! Username Password Forgot your username or password? Sign Up Already have an access code? Instructor resource file download The work is protected by local and international copyright laws and is provided solely for statisitcal use of instructors in teaching their courses and assessing student learning.

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