img Leseprobe Leseprobe

Quantitative Social Science

An Introduction in tidyverse

Kosuke Imai, Nora Webb Williams

EPUB
ca. 62,99
Amazon iTunes Thalia.de Hugendubel Bücher.de ebook.de kobo Osiander Google Books Barnes&Noble bol.com Legimi yourbook.shop Kulturkaufhaus ebooks-center.de
* Affiliatelinks/Werbelinks
Hinweis: Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.

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

Weitere Titel in dieser Kategorie

Kundenbewertungen

Schlagwörter

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