Statistical methods for the social sciences / Alan Agresti, Barbara Finlay Agresti, an introduction to statistical methods for students majoring in social science. 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. APA Citation. Agresti, A., & Finlay, B. (). Statistical methods for the social sciences (Fourth edition, Pearson new international edition.). London: Pearson.
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This edition contains several changes and additions in content, directed toward a more modern approach. The book helps in this The mathematics agresit still downplayed, in particular probability, which is all too often a stumbling block for students.
A technically correct presentation. Because of this, this book does not cover the traditional shortcut hand-computational formulas and approximations.
The book presents an introduction to statistical methods for students majoring in social science disciplines. You have successfully signed out and will be required to sign back in should you need to download more finkay.
Statistical Methods for the Social Sciences, 4th Edition
No eBook available Amazon. It provides good examples with SPSS output. My library Help Advanced Book Search. The author is successful methors his goal of introducing 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. Statistical Methods for the Social Sciences, statistifal Edition. No previous knowledge of statistics is assumed, and mathematical background is assumed to be minimal lowest-level high-school algebra.
Changes in the Fourth Edition: 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.
Perfectly reasonable base text; I think one can get through it significantly faster than two semesters, but provides just the base needed for more advanced work. It has met those expectations If you’re interested sofial creating a cost-saving package for your students, contact your Pearson rep.
Strong emphasis on regression topics. The main concepts to be understood by students are sampling distribution, confidence interval, p-value, linear regression.
Statistical Methods for the Social Sciences – Alan Agresti, Barbara Finlay – Google Books
The fourth edition has an even stronger emphasis on concepts and applications, with greater attention to “real data” both in the examples and exercises. This hhe some new exercises that ask students to use applets located at http: 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.
This item is out of print and has been replaced with Statistical Tne for the Social Sciences, 5th Edition. There is a stronger focus on real examples and on the integration of statisical software. Share a link to All Resources.
Teh text contains numerous sample printouts, mainly in the style of SPSS and occasionaly SAS, both in chapter text and homework problems. Emphasis on concepts, rather than computing formulas. Availability This item is out of print and has been replaced with Statistical Methods for the Social Sciences, 5th Edition. The book contains sufficient material for a two-semester sequence of courses. Reliance on an overly simplistic recipe-based approach to statistics is not the route to good statistical practice.
On the other hand, the text is not a cookbook. Chapter 16 includes new sections on longitudinal data analysis and multilevel hierarchical models.
Instructor resource file download 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.
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. About the Author s. Table of Contents 1. Advanced topics such as regression and ANOVA emphasize interpreting output from computer packages rather than complex computing formulas. Read, highlight, and take notes, across web, tablet, and phone.
Pearson offers special pricing when you package your text with other student resources. Students in geography, anthropology, journalism, and speech also are sometimes required to take at least one statistics course. Description The book presents an introduction to statistical methods for students majoring in social science disciplines.
He has held visiting positions sciencces 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. The main changes are as follows:. The book presents an introduction to statistical methods for students majoring in social science disciplines.
The work is protected by local and international statisticall laws and is provided solely for the use of instructors in teaching their courses and assessing student learning.
Since the first edition, the increase in computer power coupled ssocial the continued improvement and accessibility of statistical software has had a major impact on the way social scientists analyze data. The presentation of computationally complex methods, such as regression, emphasizes interpretation of software output rather than the formulas for performing the analysis.
Such sequences are commonly nad of social science graduate students in sociology, political science, and psychology. From inside the book. Such sequences are commonly required of social science graduate students in sociology, political science, and psychology. This edition has a somewhat lower technical level in the first nine chapters, to make the book more easily accessible to undergraduate students.
The author, in this new edition, uses the symbol se for estimated standard errors, rather than the notation of sigma-hat with subscript having the estimator symbol. Probability, sample data, and sampling distributions.