Gain the statistics skills you need for the social sciences with this accessible introductory guideStatistical Methods for the Social Sciences, 5th Edition,
Global Edition, by Alan Agresti, introduces you to statistical methods used in social science disciplines with no previous knowledge of statistics necessary. With an emphasis on concepts and applications, the book requires only a minimal mathematical background, maintaining a low technical level throughout to make it accessible to beginners.
The 5th edition has a strong focus on real examples to help you learn the fundamental concepts of sampling distributions, confidence intervals, and significance tests. This approach also helps you understand how to apply your learning to the real world. This edition also emphasises the interpretation of software output rather than the formulas for performing analysis, reflecting advances in statistical software - which are more frequently used by social scientists to analyse data today.
Other updates include:
Numerous homework exercises
included in each chapter.
Updated data
in most exercises.
New sections
, such as that on maximum likelihood estimation in chapter 5
New examples
ask students to use applets to help them learn the fundamental concepts of sampling distributions, confidence intervals, and significance tests.
The text also
relies more on applets
for finding tail probabilities from distributions such as the Normal, t, and chi-squared.
With a wide array of learning features and the latest available information, this text will equip you with the knowledge you need to succeed in your course - an ideal companion for students majoring in social science disciplines.
Agresti
Statistical Methods for the Social Sciences, Global Edition jetzt bestellen!
Weitere Infos & Material
Preface Acknowledgments
IntroductionSampling and MeasurementDescriptive StatisticsProbability DistributionsStatistical Inference: EstimationStatistical Inference: Significance TestsComparison of Two GroupsAnalyzing Association between Categorical VariablesLinear Regression and CorrelationIntroduction to Multivariate RelationshipsMultiple Regression and CorrelationRegression with Categorical Predictors: Analysis of Variance MethodsMultiple Regression with Quantitative and Categorical PredictorsModel Building with Multiple RegressionLogistical Regression: Modeling Categorical Responses
Appendix: R, Stata, SPSS, and SAS for Statistical Analyses Answers to Select Odd-Numbered Exercises Bibliography Credits Index
Alan Agresti
is a Distinguished Professor Emeritus in the Department of Statistics at the University of Florida. He taught statistics there for 38 years, including the development of e-courses in statistical methods for social science students and three courses in categorical data analysis.
He is the author of more than 100 refereed articles and six texts, including Statistical Methods for the Social Sciences (Pearson, 5th edition, 2018) and An Introduction to Categorical Data Analysis (Wiley, 3rd edition, 2019). Alan has also received teaching awards from the University of Florida and an Excellence in Writing award from John Wiley & Sons.
