Quantitative Social Science

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A01=Kosuke Imai
A01=Nora Webb Williams
Addition
Age Group_Uncategorized
Age Group_Uncategorized
Author_Kosuke Imai
Author_Nora Webb Williams
automatic-update
Average treatment effect
Ballot
Bias of an estimator
Binomial distribution
Blue-collar worker
Cartesian coordinate system
Category1=Non-Fiction
Category=GBC
Category=GPH
Category=JHBC
Category=UB
Category=UXJ
Causal inference
Coefficient
Conditional expectation
Conditional probability
Confidence interval
COP=United States
Coverage probability
Critical value
Data set
Delivery_Delivery within 10-20 working days
Document-term matrix
Drinking
eq_computing
eq_isMigrated=2
eq_non-fiction
eq_society-politics
Equation
Estimation
Estimator
Histogram
Ideology
Inference
Language_English
Linear regression
Measurement
Minimum wage
Newsletter
Normal distribution
Null hypothesis
Observational study
P-value
PA=Available
Parameter
Pasture
Percentage point
Politician
Prediction
Price_€100 and above
Probability
Proportionality (mathematics)
PS=Active
Pumice
Quantile
Quantity
Random variable
Randomization
Randomized experiment
Respondent
Response rate (survey)
Result
RStudio
Résumé
Sample Size
Sampling (statistics)
Sampling distribution
Sentiment analysis
Simulation
softlaunch
Standard deviation
Standard error
Standard score
Statistic
Statistical hypothesis testing
Student's t-test
Summation
Survey sampling
Types of volcanic eruptions
Uncertainty
Unemployment
Variable (computer science)
Variable (mathematics)
Variance
Voter turnout
World War II

Product details

  • ISBN 9780691222271
  • Dimensions: 178 x 254mm
  • Publication Date: 23 Aug 2022
  • Publisher: Princeton University Press
  • Publication City/Country: US
  • Product Form: Hardback
  • Language: English
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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
Kosuke Imai is Professor of Government and of Statistics at Harvard University. Nora Webb Williams is Assistant Professor of Political Science at the University of Illinois, Urbana-Champaign.