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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The main concepts to be understood by students are sampling mfthods, confidence interval, p-value, linear regression. Username Password Forgot your username or password?
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.
Integration of descriptive and inferential statistics from an early point in the text. Table of Contents 1. New to This Edition. This includes some new exercises that ask students to use applets located at http: 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.
The book presents an introduction to statistical methods for students majoring in social science disciplines. One way analysis of variance.
No eBook available Amazon. On the other hand, the text is not a cookbook. This edition has a somewhat lower technical level in the first nine chapters, to make the book more easily accessible to undergraduate students.
Sign Up Already have an access code? 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. Since the first edition, the increase in computer power coupled with the continued improvement and accessibility of statistical software has had a major impact on the way social scientists analyze data.
Chapter 16 includes new sections on longitudinal data analysis and multilevel hierarchical models. The book contains sufficient material for a two-semester sequence of courses. Strong emphasis on regression topics. The fourth edition fot an even fnlay emphasis on concepts and applications, with greater attention sciendes “real data” both statisticap the examples and exercises. This edition contains several changes and additions in content, directed toward a more modern approach.
Statistical Methods for the Social Sciences
Students in geography, anthropology, journalism, and speech also are sometimes required to take at least one statistics course. 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.
Read, highlight, and take notes, across web, tablet, and phone. 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. Emphasis on concepts, rather than computing formulas. It has met those expectations Sign In We’re sorry!
The mathematics is still downplayed, in particular probability, which is all too often a stumbling block for students. This item is out of print and has been replaced with Statistical Methods for the Social Sciences, 5th Edition.
Statistical Methods for the Social Sciences, 4th Edition
Alan AgrestiBarbara Finlay. Advanced topics such as regression and ANOVA emphasize interpreting output from computer packages rather than complex computing formulas.
Pearson offers special pricing when you package your etatistical with other student resources. If you’re interested in creating a cost-saving package for your students, contact your Pearson rep.
Statistical Methods for the Social Sciences – Alan Agresti, Barbara Finlay – Google Books
Students in geography, anthropology, journalism, and speech also are sometimes required to take at least one cor course. Statistical Methods for the Social Sciences. The book contains sufficient material for a two-semester sequence of courses. It provides good examples with SPSS output.
About the Author s. Datasets and other resources where applicable for this book are available here. Probability, sample data, and sampling distributions.
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.
Changes in the Fourth Edition: User Review – Flag as inappropriate Perfectly reasonable base text; I think one can get through it significantly soocial than two semesters, statiwtical provides just the base needed for more advanced work. Reliance on an overly simplistic recipe-based approach to statistics is not the route to good statistical practice. The author uses capital 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.
The presentation of computationally complex methods, such as regression, emphasizes interpretation of software output rather than the formulas for performing the analysis. You have successfully signed out and will be required to sign back in should you need to download more resources.
Description The book presents an introduction to statistical methods for students majoring in social science disciplines.
Account Options Sign in. Signed out You have successfully signed out and will be required to sign back in should you need to download more resources. Such sequences are commonly required of social science graduate students in sociology, political science, and psychology. Availability This item is out of print and has been replaced with Statistical Methods for the Social Sciences, 5th Edition. He has held visiting positions at Harvard University, Boston University, London School of Economics, and Sciencess College and has taught courses or short courses for universities and companies in about 20 countries worldwide.
No previous knowledge of statistics is assumed, and mathematical background is assumed to be minimal lowest-level high-school algebra.