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Produktbild: Quantitative Social Science

Quantitative Social Science An Introduction

147,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

09.02.2018

Verlag

Princeton University Press

Seitenzahl

432

Maße (L/B/H)

25,7/18/3 cm

Gewicht

1066 g

Sprache

Englisch

ISBN

978-0-691-16703-9

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

09.02.2018

Verlag

Princeton University Press

Seitenzahl

432

Maße (L/B/H)

25,7/18/3 cm

Gewicht

1066 g

Sprache

Englisch

ISBN

978-0-691-16703-9

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: GPSR Kontakt

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  • Produktbild: Quantitative Social Science

    • List of Tables
    • List of Figures
    • Preface
    • 1 Introduction
      • 1.1 Overview of the Book
      • 1.2 How to Use this Book
      • 1.3 Introduction to R
        • 1.3.1 Arithmetic Operations
        • 1.3.2 Objects
        • 1.3.3 Vectors
        • 1.3.4 Functions
        • 1.3.5 Data Files
        • 1.3.6 Saving Objects
        • 1.3.7 Packages
        • 1.3.8 Programming and Learning Tips
      • 1.4 Summary
      • 1.5 Exercises
        • 1.5.1 Bias in Self-Reported Turnout
        • 1.5.2 Understanding World Population Dynamics
      • 2 Causality
        • 2.1 Racial Discrimination in the Labor Market
        • 2.2 Subsetting the Data in R
          • 2.2.1 Logical Values and Operators
          • 2.2.2 Relational Operators
          • 2.2.3 Subsetting
          • 2.2.4 Simple Conditional Statements
          • 2.2.5 Factor Variables
        • 2.3 Causal Effects and the Counterfactual
        • 2.4 Randomized Controlled Trials
          • 2.4.1 The Role of Randomization
          • 2.4.2 Social Pressure and Voter Turnout
        • 2.5 Observational Studies
          • 2.5.1 Minimum Wage and Unemployment
          • 2.5.2 Confounding Bias
          • 2.5.3 Before-and-After and Difference-in-Differences Designs
        • 2.6 Descriptive Statistics for a Single Variable
          • 2.6.1 Quantiles
          • 2.6.2 Standard Deviation
        • 2.7 Summary
        • 2.8 Exercises
          • 2.8.1 Efficacy of Small Class Size in Early Education
          • 2.8.2 Changing Minds on Gay Marriage
          • 2.8.3 Success of Leader Assassination as a Natural Experiment
        • 3 Measurement
          • 3.1 Measuring Civilian Victimization during Wartime
          • 3.2 Handling Missing Data in R
          • 3.3 Visualizing the Univariate Distribution
            • 3.3.1 Bar Plot
            • 3.3.2 Histogram
            • 3.3.3 Box Plot
            • 3.3.4 Printing and Saving Graphs
          • 3.4 Survey Sampling
            • 3.4.1 The Role of Randomization
            • 3.4.2 Nonresponse and Other Sources of Bias
          • 3.5 Measuring Political Polarization
          • 3.6 Summarizing Bivariate Relationships
            • 3.6.1 Scatter Plot
            • 3.6.2 Correlation
            • 3.6.3 Quantile-Quantile Plot
          • 3.7 Clustering
            • 3.7.1 Matrix in R
            • 3.7.2 List in R
            • 3.7.3 The k-Means Algorithm
          • 3.8 Summary
          • 3.9 Exercises
            • 3.9.1 Changing Minds on Gay Marriage: Revisited
            • 3.9.2 Political Efficacy in China and Mexico
            • 3.9.3 Voting in the United Nations General Assembly
          • 4 Prediction
            • 4.1 Predicting Election Outcomes
              • 4.1.1 Loops in R
              • 4.1.2 General Conditional Statements in R
              • 4.1.3 Poll Predictions
            • 4.2 Linear Regression
              • 4.2.1 Facial Appearance and Election Outcomes
              • 4.2.2 Correlation and Scatter Plots
              • 4.2.3 Least Squares
              • 4.2.4 Regression towards the Mean
              • 4.2.5 Merging Data Sets in R
              • 4.2.6 Model Fit
            • 4.3 Regression and Causation
              • 4.3.1 Randomized Experiments
              • 4.3.2 Regression with Multiple Predictors
              • 4.3.3 Heterogeneous Treatment Effects
              • 4.3.4 Regression Discontinuity Design
            • 4.4 Summary
            • 4.5 Exercises
              • 4.5.1 Prediction Based on Betting Markets
              • 4.5.2 Election and Conditional Cash Transfer Program in Mexico
              • 4.5.3 Government Transfer and Poverty Reduction in Brazil
            • 5 Discovery
              • 5.1 Textual Data
                • 5.1.1 The Disputed Authorship of The Federalist Papers
                • 5.1.2 Document-Term Matrix
                • 5.1.3 Topic Discovery
                • 5.1.4 Authorship Prediction
                • 5.1.5 Cross Validation
              • 5.2 Network Data
                • 5.2.1 Marriage Network in Renaissance Florence
                • 5.2.2 Undirected Graph and Centrality Measures
                • 5.2.3 Twitter-Following Network
                • 5.2.4 Directed Graph and Centrality
              • 5.3 Spatial Data
                • 5.3.1 The 1854 Cholera Outbreak in London
                • 5.3.2 Spatial Data in R
                • 5.3.3 Colors in R
                • 5.3.4 US Presidential Elections
                • 5.3.5 Expansion of Walmart
                • 5.3.6 Animation in R
              • 5.4 Summary
              • 5.5 Exercises
                • 5.5.1 Analyzing the Preambles of Constitutions
                • 5.5.2 International Trade Network
                • 5.5.3 Mapping US Presidential Election Results over Time
              • 6 Probability
                • 6.1 Probability
                  • 6.1.1 Frequentist versus Bayesian
                  • 6.1.2 Definition and Axioms
                  • 6.1.3 Permutations
                  • 6.1.4 Sampling with and without Replacement
                  • 6.1.5 Combinations
                • 6.2 Conditional Probability
                  • 6.2.1 Conditional, Marginal, and Joint Probabilities
                  • 6.2.2 Independence
                  • 6.2.3 Bayes’ Rule
                  • 6.2.4 Predicting Race Using Surname and Residence Location
                • 6.3 Random Variables and Probability Distributions
                  • 6.3.1 Random Variables
                  • 6.3.2 Bernoulli and Uniform Distributions
                  • 6.3.3 Binomial Distribution
                  • 6.3.4 Normal Distribution
                  • 6.3.5 Expectation and Variance
                  • 6.3.6 Predicting Election Outcomes with Uncertainty
                • 6.4 Large Sample Theorems
                  • 6.4.1 The Law of Large Numbers
                  • 6.4.2 The Central Limit Theorem
                • 6.5 Summary
                • 6.6 Exercises
                  • 6.6.1 The Mathematics of Enigma
                  • 6.6.2 A Probability Model for Betting Market Election Prediction
                  • 6.6.3 Election Fraud in Russia
                • 7 Uncertainty
                  • 7.1 Estimation
                    • 7.1.1 Unbiasedness and Consistency
                    • 7.1.2 Standard Error
                    • 7.1.3 Confidence Intervals
                    • 7.1.4 Margin of Error and Sample Size Calculation in Polls
                    • 7.1.5 Analysis of Randomized Controlled Trials
                    • 7.1.6 Analysis Based on Student’s t-Distribution
                  • 7.2 Hypothesis Testing
                    • 7.2.1 Tea-Tasting Experiment
                    • 7.2.2 The General Framework
                    • 7.2.3 One-Sample Tests
                    • 7.2.4 Two-Sample Tests
                    • 7.2.5 Pitfalls of Hypothesis Testing
                    • 7.2.6 Power Analysis
                  • 7.3 Linear Regression Model with Uncertainty
                    • 7.3.1 Linear Regression as a Generative Model
                    • 7.3.2 Unbiasedness of Estimated Coefficients
                    • 7.3.3 Standard Errors of Estimated Coefficients
                    • 7.3.4 Inference about Coefficients
                    • 7.3.5 Inference about Predictions
                  • 7.4 Summary
                  • 7.5 Exercises
                    • 7.5.1 Sex Ratio and the Price of Agricultural Crops in China
                    • 7.5.2 File Drawer and Publication Bias in Academic Research
                    • 7.5.3 The 1932 German Election in the Weimar Republic
                  • 8 Next
                  • General Index
                  • R Index