Vor Ort
Merkzettel Warenkorb
Produktbild: Data Analysis for Social Science

Data Analysis for Social Science A Friendly and Practical Introduction

62,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

29.11.2022

Abbildungen

57 color + 101 b/w illus. 33 tables.

Verlag

University Presses

Seitenzahl

256

Maße (L/B/H)

25,1/20,1/1,5 cm

Gewicht

614 g

Sprache

Englisch

ISBN

978-0-691-19943-6

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

29.11.2022

Abbildungen

57 color + 101 b/w illus. 33 tables.

Verlag

University Presses

Seitenzahl

256

Maße (L/B/H)

25,1/20,1/1,5 cm

Gewicht

614 g

Sprache

Englisch

ISBN

978-0-691-19943-6

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

Noch keine Bewertungen vorhanden

Verfassen Sie die erste Bewertung zu diesem Artikel

Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.

Kundinnen und Kunden meinen

Bewertungen (0)
Die Leseprobe wird geladen.
  • Produktbild: Data Analysis for Social Science

    • Preface
    • 1 Introduction
      • 1.1 Book Overview
      • 1.2 Chapter Summaries
      • 1.3 How to Use This Book
      • 1.4 Why Learn to Analyze Data?
        • 1.4.1 Learning to Code
        • 1.5 Getting Ready
        • 1.6 Introduction to R
          • 1.6.1 Doing Calculations in R
          • 1.6.2 Creating Objects in R
          • 1.6.3 Using Functions in R
          • 1.7 Loading and Making Sense of Data
            • 1.7.1 Setting the Working Directory
            • 1.7.2 Loading the Dataset
            • 1.7.3 Understanding the Data
            • 1.7.4 Identifying the Types of Variables Included
            • 1.7.5 Identifying the Number of Observations
            • 1.8 Computing and Interpreting Means
              • 1.8.1 Accessing Variables inside Dataframes
              • 1.8.2 Means
              • 1.9 Summary
              • 1.10 Cheatsheets
                • 1.10.1 Concepts and Notation
                • 1.10.2 R Symbols and Operators
                • 1.10.3 R Functions
                • 2 Estimating Causal Effects with Randomized Experiments
                  • 2.1 Project STAR
                  • 2.2 Treatment and Outcome Variables
                    • 2.2.1 Treatment Variables
                    • 2.2.2 Outcome Variables
                    • 2.3 Individual Causal Effects
                    • 2.4 Average Causal Effects
                      • 2.4.1 Randomized Experiments and the Difference-in-Means Estimator
                      • 2.5 Do Small Classes Improve Student Performance?
                        • 2.5.1 Relational Operators in R
                        • 2.5.2 Creating New Variables
                        • 2.5.3 Subsetting Variables
                        • 2.6 Summary
                        • 2.7 Cheatsheets
                          • 2.7.1 Concepts and Notation
                          • 2.7.2 R Symbols and Operators
                          • 2.7.3 R Functions
                          • 3 Inferring Population Characteristics via Survey Research
                            • 3.1 The EU Referendum in the UK
                            • 3.2 Survey Research
                              • 3.2.1 Random Sampling
                              • 3.2.2 Potential Challenges
                              • 3.3 Measuring Support for Brexit
                                • 3.3.1 Predicting the Referendum Outcome
                                • 3.3.2 Frequency Tables
                                • 3.3.3 Tables of Proportions
                                • 3.4 Who Supported Brexit?
                                  • 3.4.1 Handling Missing Data
                                  • 3.4.2 Two-Way Frequency Tables
                                  • 3.4.3 Two-Way Tables of Proportions
                                  • 3.4.4 Histograms
                                  • 3.4.5 Density Histograms
                                  • 3.4.6 Descriptive Statistics
                                  • 3.5 Relationship between Education and the LeaveVote in the Entire UK
                                    • 3.5.1 Scatter Plots
                                    • 3.5.2 Correlation
                                    • 3.6 Summary
                                    • 3.7 Cheatsheets
                                      • 3.7.1 Concepts and Notation
                                      • 3.7.2 R Symbols and Operators
                                      • 3.7.3 R Functions
                                      • 4 Predicting Outcomes Using Linear Regression
                                        • 4.1 GDP and Night-Time Light Emissions
                                        • 4.2 Predictors, Observed vs. Predicted Outcomes, andPrediction Errors
                                        • 4.3 Summarizing the Relationship between Two Variables with a Line
                                          • 4.3.1 The Linear Regression Model
                                          • 4.3.2 The Intercept Coefficient
                                          • 4.3.3 The Slope Coefficient
                                          • 4.3.4 The Least Squares Method
                                          • 4.4 Predicting GDP Using Prior GDP
                                            • 4.4.1 Relationship between GDP and Prior GDP
                                            • 4.4.2 With Natural Logarithm Transformations
                                            • 4.5 Predicting GDP Growth Using Night-Time LightEmissions
                                            • 4.6 Measuring How Well the Model Fits the Data with the Coefficient of Determination, R2
                                              • 4.6.1 How Well Do the Three Predictive Modelsin This Chapter Fit the Data?
                                              • 4.7 Summary
                                              • 4.8 Appendix: Interpretation of the Slope in the Log-Log Linear Model
                                              • 4.9 Cheatsheets
                                                • 4.9.1 Concepts and Notation
                                                • 4.9.2 R Functions
                                                • 5 Estimating Causal Effects with Observational Data
                                                  • 5.1 Russian State-Controlled TV Coverage of 2014Ukrainian Affairs
                                                  • 5.2 Challenges of Estimating Causal Effects withObservational Data
                                                    • 5.2.1 Confounding Variables
                                                    • 5.2.2 Why Are Confounders a Problem?
                                                    • 5.2.3 Confounders in Randomized Experiments
                                                    • 5.3 The Effect of Russian TV on Ukrainians’ VotingBehavior
                                                      • 5.3.1 Using the Simple Linear Model to Computethe Difference-in-Means Estimator
                                                      • 5.3.2 Controlling for Confounders Using aMultiple Linear Regression Model
                                                      • 5.4 The Effect of Russian TV on Ukrainian ElectoralOutcomes
                                                        • 5.4.1 Using the Simple Linear Model to Computethe Difference-in-Means Estimator
                                                        • 5.4.2 Controlling for Confounders Using aMultiple Linear Regression Model
                                                        • 5.5 Internal and External Validity
                                                          • 5.5.1 Randomized Experiments vs.Observational Studies
                                                          • 5.5.2 The Role of Randomization
                                                          • 5.5.3 How Good Are the Two Causal Analysesin This Chapter?
                                                          • 5.5.4 How Good Was the Causal Analysis inChapter 2?
                                                          • 5.5.5 The Coefficient of Determination, R2
                                                          • 5.6 Summary
                                                          • 5.7 Cheatsheets
                                                            • 5.7.1 Concepts and Notation
                                                            • 5.7.2 R Functions
                                                            • 6 Probability
                                                              • 6.1 What Is Probability?
                                                              • 6.2 Axioms of Probability
                                                              • 6.3 Events, Random Variables, and ProbabilityDistributions
                                                              • 6.4 Probability Distributions
                                                                • 6.4.1 The Bernoulli Distribution
                                                                • 6.4.2 The Normal Distribution
                                                                • 6.4.3 The Standard Normal Distribution
                                                                • 6.4.4 Recap
                                                                • 6.5 Population Parameters vs. Sample Statistics
                                                                  • 6.5.1 The Law of Large Numbers
                                                                  • 6.5.2 The Central Limit Theorem
                                                                  • 6.5.3 Sampling Distribution of the Sample Mean
                                                                  • 6.6 Summary
                                                                  • 6.7 Appendix: For Loops
                                                                  • 6.8 Cheatsheets
                                                                    • 6.8.1 Concepts and Notation
                                                                    • 6.8.2 R Symbols and Operators
                                                                    • 6.8.3 R Functions
                                                                    • 7 Quantifying Uncertainty
                                                                      • 7.1 Estimators and Their Sampling Distributions
                                                                      • 7.2 Confidence Intervals
                                                                        • 7.2.1 For the Sample Mean
                                                                        • 7.2.2 For the Difference-in-Means Estimator
                                                                        • 7.2.3 For Predicted Outcomes
                                                                        • 7.3 Hypothesis Testing
                                                                          • 7.3.1 With the Difference-in-Means Estimator
                                                                          • 7.3.2 With Estimated Regression Coefficients
                                                                          • 7.4 Statistical vs. Scientific Significance
                                                                          • 7.5 Summary
                                                                          • 7.6 Cheatsheets
                                                                            • 7.6.1 Concepts and Notation
                                                                            • 7.6.2 R Symbols and Operators
                                                                            • 7.6.3 R Functions
                                                                            • Index of Concepts
                                                                            • Index of Mathematical Notation
                                                                            • Index of R and RStudio