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Data analysis for social science : a friendly and practical introduction /

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? 1.5 Getting Ready 1.6 Introduction to R 1.7 Loading and Making Sense of Data 1.8 Computing and Interpreting Means 2 - Estimating Cusal Effects with Randomized Experiments 2.1 P...

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Main Authors: Llaudet, Elena, Imai, Kosuke
Format: Livro Geral
Language:Português
Published: 2023
Subjects:
Ciências Sociais - Métodos Estatísticos
Estudos Científicos Sociais
Conceitos Estatísticos
Online Access:https://acervo.enap.gov.br/cgi-bin/koha/opac-detail.pl?biblionumber=524387
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id KOHA-OAI-ENAP:524387
recordtype KOHA
first_indexed 2024-03-19T10:04:06Z
last_indexed 2024-03-19T10:04:06Z
spelling KOHA-OAI-ENAP:5243872023-08-16T14:01:39Z nam a22 7a 4500 524387 524500 BR-BrENAP 20230713121819.0 230713b xxu||||| |||| 00| 0 por d 9780691199436 BR-BrENAP Pt_BR eng 001.422 L7914d Llaudet, Elena 68245 Data analysis for social science : a friendly and practical introduction / por Elena Llaudet e Kosuke Imai. -- Nova Jersey, EUA : Princeton University Press, 2023. 238 p. 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? 1.5 Getting Ready 1.6 Introduction to R 1.7 Loading and Making Sense of Data 1.8 Computing and Interpreting Means 2 - Estimating Cusal Effects with Randomized Experiments 2.1 Project STAR 2.2 Treatment and Outcome Variables 2.3 Individual Causal Effects 2.4 Average Causal Effects 2.5 Do Small Classes Improve Student Perfomance? 3 - Inferring Population Characteristiics via Survey Research 3.1 The EU Referendum in the UK 3.2 Survey Research 3.3 Measuring Support for Brexit 3.4 Who Supported Brexit? 3.5 Relationship between Education and the Leave Vote in the Entire UK 4 - Predicting Outcomes Using Linear Regression 4.1 GDP and Night-Time Light Emissions 4.2 Predictions, Observed vs. Predicted Outcomes, and Prediction Errors 4.3 Summarizing the Relationship between Two Variables with a Line 4.4 Predicting GDP Using Prior GDP 4.5 Predicting GDP Growth Using Night-Time Light Emissions 4.6 Measuring How Well the Model Fits the Data with thCoefficient of Determination, R² 5 - Estimating Causal Effects with Observational Data 5.1 Russian State-Controlled TV Coverage of 2014 Ukrainian 5.2 Challenges of Estimating Causal Effects with Observational Data 5.3 The Effect of Russian TV on Ukrainians' Voting Behavior 5.4 The Effect of Russian TV Russian TV on Ukrainian Electoral Outcomes 5.5 Internal and External Validity 6 - Probability 6.1 What Is Probability? 6.2 Axioms of Probability 6.3 Events, Random Variables, and Probability Distributions 6.4 Probability Distributions 6.5 Population Parameters vs. Sample Statistics 7 - Quantifying Uncertainty 7.1 Estimators and Their Sampling Distributions 7.2 Confidence Intervals 7.4 Statistical vs. Scientific Significance Index of Concepts Index of Mathematical Notation Index of R and RStudio Ciências Sociais - Métodos Estatísticos 68246 Estudos Científicos Sociais 68247 Conceitos Estatísticos 68248 Imai, Kosuke 24443 202307 Raynara G
institution ENAP-Escola Nacional de Administração Pública
collection Biblioteca Graciliano Ramos
language Português
topic Ciências Sociais - Métodos Estatísticos
Estudos Científicos Sociais
Conceitos Estatísticos
spellingShingle Ciências Sociais - Métodos Estatísticos
Estudos Científicos Sociais
Conceitos Estatísticos
Llaudet, Elena
Imai, Kosuke
Data analysis for social science : a friendly and practical introduction /
topic_facet Ciências Sociais - Métodos Estatísticos
Estudos Científicos Sociais
Conceitos Estatísticos
description 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? 1.5 Getting Ready 1.6 Introduction to R 1.7 Loading and Making Sense of Data 1.8 Computing and Interpreting Means 2 - Estimating Cusal Effects with Randomized Experiments 2.1 Project STAR 2.2 Treatment and Outcome Variables 2.3 Individual Causal Effects 2.4 Average Causal Effects 2.5 Do Small Classes Improve Student Perfomance? 3 - Inferring Population Characteristiics via Survey Research 3.1 The EU Referendum in the UK 3.2 Survey Research 3.3 Measuring Support for Brexit 3.4 Who Supported Brexit? 3.5 Relationship between Education and the Leave Vote in the Entire UK 4 - Predicting Outcomes Using Linear Regression 4.1 GDP and Night-Time Light Emissions 4.2 Predictions, Observed vs. Predicted Outcomes, and Prediction Errors 4.3 Summarizing the Relationship between Two Variables with a Line 4.4 Predicting GDP Using Prior GDP 4.5 Predicting GDP Growth Using Night-Time Light Emissions 4.6 Measuring How Well the Model Fits the Data with thCoefficient of Determination, R² 5 - Estimating Causal Effects with Observational Data 5.1 Russian State-Controlled TV Coverage of 2014 Ukrainian 5.2 Challenges of Estimating Causal Effects with Observational Data 5.3 The Effect of Russian TV on Ukrainians' Voting Behavior 5.4 The Effect of Russian TV Russian TV on Ukrainian Electoral Outcomes 5.5 Internal and External Validity 6 - Probability 6.1 What Is Probability? 6.2 Axioms of Probability 6.3 Events, Random Variables, and Probability Distributions 6.4 Probability Distributions 6.5 Population Parameters vs. Sample Statistics 7 - Quantifying Uncertainty 7.1 Estimators and Their Sampling Distributions 7.2 Confidence Intervals 7.4 Statistical vs. Scientific Significance Index of Concepts Index of Mathematical Notation Index of R and RStudio
format Livro Geral
author Llaudet, Elena
Imai, Kosuke
author_facet Llaudet, Elena
Imai, Kosuke
author_sort Llaudet, Elena
title Data analysis for social science : a friendly and practical introduction /
title_short Data analysis for social science : a friendly and practical introduction /
title_full Data analysis for social science : a friendly and practical introduction /
title_fullStr Data analysis for social science : a friendly and practical introduction /
title_full_unstemmed Data analysis for social science : a friendly and practical introduction /
title_sort data analysis for social science : a friendly and practical introduction /
publishDate 2023
url https://acervo.enap.gov.br/cgi-bin/koha/opac-detail.pl?biblionumber=524387
isbn 9780691199436
_version_ 1793948538617462784
score 10.920854

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