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.
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Alan Agresti is Distinguished Professor in the Department of Statistics at the University of Florida. He has been teaching statistics there for 35 years, including the development of three courses in statistical methods for social science students and three courses in categorical data analysis. He is author of over 100 refereed article and five texts including "Statistical Methods for the Social Sciences" (with Barbara Finlay, Prentice Hall, 4th edition 2009) and "Categorical Data Analysis" (Wiley, 2nd edition 2002). He is a Fellow of the American Statistical Association and recipient of an Honorary Doctor of Science from De Montfort University in the UK. In 2003 Alan was named "Statistician of the Year" by the Chicago chapter of the American Statistical Association and in 2004 he was the first honoree of the Herman Callaert Leadership Award in Biostatistical Education and Dissemination awarded by the University of Limburgs, Belgium. 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 30 countries worldwide. Alan has also received teaching awards from UF and an excellence in writing award from John Wiley & Sons. Christine Franklin is a Senior Lecturer and Honors Professor in the Department of Statistics at the University of Georgia. She has been a member of college faculty in statistics for almost 30 years. Chris has been actively involved at the national level with promoting statistical education at the K-12 level and college undergraduate level since the 1980's. She is currently the Chief Reader for AP Statistics and has developed threemasters level courses at UGA in data analysis for elementary, middle school, and secondary teachers. Chris was the lead writer for the ASA endorsed Guidelines for Assessment and Instruction in Statistics Education (GAISE) Report: A Pre-K-12 Curriculum Framework. Chris has been honored by her selection as a Fellow of the American Statistical Association, the 2006 Mu Sigma Rho National Statistical Education Award recipient for her teaching and lifetime devotion to statistics education, and numerous teaching and advising awards at UGA. Chris has written more than 30 journal articles and resource materials for textbooks.
"This text is readable, understandable, and well-organized. It provides good examples with SPSS output." (Robert Wilson, University of Delaware). "Overall, [Agresti/ Finlay] is a good book for introductory statistics that targets general audiences...it covers most topics you want to cover and allows the instructor to choose which topics to include." (Youqin Huang, State University of New York, Albany) "I originally started using the Agresti/ Finlay book based on its reputation as "the class of the market," in terms of being unfailingly statistically correct and having a "modern" perspective. 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..." (Michael Lacey, Colorado State University) .,"the book has been a good and helpful resource for me in preparing the class notes and assigning homework qustions. The main concepts to be understood by students are sampling distribution, confidence interval, p-value, linear regression. The book helps in this..." (Arne Bathke, University of Kentucky)
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