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Quantitative Social Science

An Introduction in tidyverse

Kosuke Imai, Nora Webb Williams

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Princeton University Press img Link Publisher

Sozialwissenschaften, Recht, Wirtschaft / Methoden der empirischen und qualitativen Sozialforschung

Beschreibung

A tidyverse edition of the acclaimed textbook on data analysis and statistics for the social sciences and allied fields

Quantitative analysis is an essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it. Quantitative Social Science is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, including business, economics, education, political science, psychology, sociology, public policy, and data science. Proven in classrooms around the world, this one-of-a-kind textbook engages directly with empirical analysis, showing students how to analyze and interpret data using the tidyverse family of R packages. Data sets taken directly from leading quantitative social science research illustrate how to use data analysis to answer important questions about society and human behavior.

  • Emphasizes hands-on learning, not paper-and-pencil statistics
  • Includes data sets from actual research for students to test their skills on
  • Covers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools
  • Features a wealth of supplementary exercises, including additional data analysis exercises and programming exercises
  • Offers a solid foundation for further study
  • Comes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides

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Addition, Variance, Data set, Histogram, World War II, Standard score, Respondent, Inference, Simulation, Randomization, Unemployment, Minimum wage, Standard deviation, Survey sampling, Null hypothesis, Pasture, Estimation, Drinking, Conditional expectation, Quantile, Quantity, Normal distribution, Percentage point, Sentiment analysis, Conditional probability, Critical value, Average treatment effect, Sampling distribution, Politician, Causal inference, Ideology, Linear regression, Prediction, Coverage probability, Response rate (survey), Statistic, Statistical hypothesis testing, Voter turnout, Random variable, Résumé, Coefficient, Parameter, Equation, Blue-collar worker, Measurement, Types of volcanic eruptions, Bias of an estimator, Uncertainty, Variable (computer science), Ballot, Probability, Estimator, Proportionality (mathematics), Binomial distribution, Sample Size, Pumice, P-value, Randomized experiment, Cartesian coordinate system, Sampling (statistics), Document-term matrix, Observational study, Standard error, Newsletter, Student's t-test, RStudio, Summation, Variable (mathematics), Confidence interval, Result