Quantitative Social Science (eBook)

An Introduction

Kosuke Imai (Autor)

eBook Download: EPUB

2024
718 Seiten
Princeton University Press (Verlag)
9780691270838 (ISBN)

Infos

An introductory textbook on data analysis and statistics written especially for students in the social sciences and allied fieldsQuantitative analysis is an increasingly essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it-or if they do, they usually end up in statistics classes that offer few insights into their field. This textbook is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, such as economics, sociology, public policy, and data science.Quantitative Social Science engages directly with empirical analysis, showing students how to analyze data using the R programming language and to interpret the results-it encourages hands-on learning, not paper-and-pencil statistics. More than forty data sets taken directly from leading quantitative social science research illustrate how data analysis can be used to answer important questions about society and human behavior.Proven in the classroom, this one-of-a-kind textbook features numerous additional data analysis exercises and interactive R programming exercises, and also comes with supplementary teaching materials for instructors.Written especially for students in the social sciences and allied fields, including economics, sociology, public policy, and data scienceProvides hands-on instruction using R programming, not paper-and-pencil statisticsIncludes more than forty data sets from actual research for students to test their skills onCovers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical toolsFeatures a wealth of supplementary exercises, including additional data analysis exercises and interactive programming exercisesOffers a solid foundation for further studyComes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slidesLooking for a more accessible introduction? Consider Data Analysis for Social Science by Elena Llaudet and Kosuke Imai, which teaches from scratch and step-by-step the fundamentals of survey research, predictive models, and causal inference. It covers descriptive statistics, the difference-in-means estimator, simple linear regression, and multiple linear regression.

Produkt-Details

• Erscheint lt. Verlag: 10.9.2024
• Zusatzinfo: 14 color illus. 9 halftones. 77 line illus.
• Sprache: englisch
• Themenwelt: Sozialwissenschaften ► Politik / Verwaltung
• Themenwelt: Sozialwissenschaften ► Soziologie ► Empirische Sozialforschung
• Schlagworte: Accuracy and precision • Addition • Alternative hypothesis • average treatment effect • Bayesian • Bernoulli distribution • betweenness • Bias of an estimator • Binomial Distribution • birthday problem • Box Plot • Calculation • Cartesian coordinate system • causal inference • central limit theorem • coefficient • coefficient of determination • combination • Conditional probability • Confidence interval • confounding • Correlation and dependence • Cross-validation (statistics) • data set • Empirical distribution function • Equation • error • Error Term • estimation • Estimator • expected value • Exploratory data analysis • Fair coin • False Discovery Rate • Fisher's Exact Test • histogram • inference • internal validity • Interquartile range • Joint probability distribution • K-means clustering • law of large numbers • Law of total variance • Least Squares • linear regression • margin of error • Measurement • minimum wage • Monte Carlo Method • Multiple comparisons problem • Mutual exclusivity • Normal distribution • null hypothesis • observational study • One-Tailed Test • Pagerank • Parameter (computer programming) • percentage • Percentage point • Permutation • Point Estimation • Population proportion • Prediction • Probability • Probability Distribution • Proportionality (mathematics) • p-value • Quantile • Quartile • Randomization • Randomized experiment • Random Variable • regression discontinuity design • Regression toward the mean • result • Sample space • Sampling (Statistics) • standard deviation • standard error • Standard Score • Statistic • Statistical hypothesis testing • statistical significance • Student's T-Distribution • Student's t-test • Summation • test statistic • Type I and type II errors • Uncertainty • Variable (computer science) • Variable (mathematics) • Variance • Weighted arithmetic mean • Z-Test
• ISBN-13: 9780691270838 / 9780691270838