A stata companion to political analysis:
The Fifth Edition of A Stata® Companion to Political Analysis by Philip H. Pollock III and Barry C. Edwards teaches your students statistics by analyzing research-quality data in Stata. It follows the structure of Essentials of Political Analysis with software instructions, explanations of t...
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| Zusammenfassung: | The Fifth Edition of A Stata® Companion to Political Analysis by Philip H. Pollock III and Barry C. Edwards teaches your students statistics by analyzing research-quality data in Stata. It follows the structure of Essentials of Political Analysis with software instructions, explanations of tests, and many exercises for practice |
| Beschreibung: | xxxiv, 365 Seiten Illustrationen, Diagramme 1112 grams |
| ISBN: | 9781071815045 |
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| 245 | 1 | 0 | |a A stata companion to political analysis |c Philip H. Pollock III, University of Central Florida, Barry C. Edwards, University of Central Florida |
| 250 | |a Fifth edition | ||
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| 520 | |a The Fifth Edition of A Stata® Companion to Political Analysis by Philip H. Pollock III and Barry C. Edwards teaches your students statistics by analyzing research-quality data in Stata. It follows the structure of Essentials of Political Analysis with software instructions, explanations of tests, and many exercises for practice | ||
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Datensatz im Suchindex
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| adam_text | BRIEF CONTENTS List of Boxes xiii List of Figures xv List of Tables xix Preface xxi Acknowledgments xxv xxvii Introduction Chapter 1 Using Stata for Data Analysis Chapter 2 Descriptive Statistics 17 Chapters Transforming Variables 37 Chapter 4 Making Comparisons 61 Chapter 5 Graphing Relationships and Describing Patterns 83 Chapter 6 Random Assignment and Sampling 111 Chapter 7 Making Controlled Comparisons 133 Chapters Foundations of Statistical Inference 151 Chapter 9 Hypothesis Tests with One or Two Samples 169 Chapter 10 Chi-Square Test and Analysis of Variance 187 Chapter 11 Correlation and Bivariate Regression 213 Chapter 12 Multiple Regression 229 Chapter 13 Analyzing Regression Residuals 249 Chapter 14 Logistic Regression 269 Chapter 15 Doing Your Own Political Analysis 299 1 Appendix, Table A-1 - Variables in the Debate Experiment Dataset 317 Appendix, Table A-2 - Variables in the GSS Dataset in Alphabetical Order 319 Appendix, Table A-3 - Variables in the NES Dataset in Alphabetical Order 333 Appendix, Table A-4 - Variables in the States Dataset by Topic 345 Appendix, Table A-5 - Variables in the World Dataset by Topic 351 Glossary 361
DETAILED CONTENTS List of Boxes xiii List of Figures xv List of Tables xix Preface xxi Acknowledgments xxv xxvii Introduction Chapter 1 Using Stata for Data Analysis 1.1 General Syntax of Stata Commands 1 2 1.2 Using Stata s Graphical User Interface Effectively 4 1.3 Do-files 4 1.4 Printing Results and Copying Output 8 1.5 Customizing Your Display 11 1.6 Log Files 12 1.7 Getting Help 13 Key Terms 15 Chapter 1 Exercises 15 Chapter 2 Descriptive Statistics 17 2.1 Identifying Levels of Measurement 18 2.2 Describing Nominal Variables 19 2.3 Describing Ordinal Variables 21 2.4 Bar Charts for Nominal and Ordinal Variables 23 2.5 Describing Interval Variables 25 2.6 Histograms for Interval Variables 29 2.7 Obtaining Case-Level Information 31 Key Terms 33 Chapter 2 Exercises 33 Chapters Transforming Variables 37 3.1 Creating Dummy Variables 38 3.2 Applying Mathematical Operators to Variables 42 3.3 Managing Variable Descriptions and Labels 46 3.3.1 Modifying Variable Labels Using Commands 3.3.2 Modifying Variable Labels with Stata’s Variables Manager 46 47 3.4 Collapsing Variables into Simplified Categories 50 3.5 Centering or Standardizing a Numeric Variable 53 3.6 Creating an Additive Index 54 Key Terms 57 Chapter 3 Exercises 57
viii A Stata® Companion to Political Analysis Making Comparisons Chapter 4 4.1 Cross-Tabulation Analysis 61 62 4.1.1 Generating a Cross-Tabulation 4.1.2 Interpreting Cross-Tabulation Analysis 63 64 4.1.3 Cross-Tabulation with Weighted Observations 4.1.4 Visualizing Cross-Tabulation Analysis with Simple Bar Charts 64 66 4.2 Mean Comparison Analysis 4.2.1 Generating a Mean Comparison Table 69 4.2.2 Interpreting Mean Comparison Analysis 4.2.3 Comparing Means with Weighted Observations 70 70 71 4.2.4 Visualizing Mean Comparisons with Box Plots 74 4.3 Making Comparisons with Interval-Level Independent Variables 77 Key Terms 78 Chapter 4 Exercises 78 Chapter 5 Graphing Relationships and Describing Patterns 5.1 Graphs for Binary Dependent Variables 83 85 5.1.1 Simple Bar Charts with Nominal-Level Independent Variables 85 5.1.2 Area Chart with Ordinal-Level Independent Variables 87 5.1.3 Graphs with Interval-Level Independent Variables 88 5.2 Graphs for Nominal-Level Dependent Variables 90 5.2.1 Clustered Bar Charts with Nominal Independent Variables 90 5.2.2 Multiple Line Plots with Ordinal Independent Variables 92 5.2.3 Graphs with Interval-Level Independent Variables 93 5.3 Graphs for Ordinal-Level Dependent Variables 94 5.3.1 Using Bars to Represent Select Values 94 5.3.2 Stacked Bar Chart for an Ordinal-Ordinal Relationship 96 5.3.3 Graphs with Interval-Level Independent Variables 98 5.4 Graphs for Interval-Level Dependent Variables 5.4.1 Plotting Means with Bars or Lines 101 102 5.4.2 Box Plots 102 5.4.3 Scatterplots 103 Key Terms 107 Chapter 5 Exercises 107 Chapter 6 Random
Assignment and Sampling 6.1 Random Assignment 6.1.1 Two Groups with Equal Probability 112 112 6.1.2 Multiple Groups with Varying Probabilities 113 6.1.3 Random Assignment to Predetermined Size Groups 115 6.2 Analyzing the Results of an Experiment 6.3 111 118 6.2.1 Assessing Random Assignment 119 6.2.2 Evaluating the Effect of Treatment 120 Random Sampling 121 6.3.1 Simple Random Samples with Replacement 121 6.3.2 Simple Random Samples without Replacement 6.3.3 Systematic Random Samples 122 122 6.3.4 Clustered and Stratified Random Samples 124 6.4 Selecting Cases for Qualitative Analysis 125 6.4.1 Most Similar Systems 125 6.4.2 Most Different Systems 127 6.5 Analyzing Data Ethically 128 6.5.1 Ethical Issues in Data Analysis 128 6.5.2 Ten Tips for Writing Replication Do-files 129
Detailed Contents Key Terms 130 Chapter 6 Exercises Chapter 7 7.1 Making Controlled Comparisons 130 133 Cross-Tabulation Analysis with a Control Variable 134 7.1.1 Start with a Basic Cross-Tabulation 7.1.2 Controlling for Another Variable 134 135 7.1.3 Interpreting Controlled Cross-Tabulations 137 7.2 Visualizing Controlled Comparisons with Categorical Dependent Variables 139 7.3 Mean Comparison Analysis with a Control Variable 142 7.3.1 Start with a Basic Mean Comparison Table 7.3.2 Adding Control Variables 142 7.3.3 Interpreting a Controlled Mean Comparison 143 142 7.4 Visualizing Controlled Mean Comparisons 143 KeyTerms 146 Chapter 7 Exercises 146 Chapters Foundations of Statistical Inference 151 8.1 Estimating Population Parameters with Simulations 152 8.2 Expected Shape of Sampling Distributions 155 8.2.1 8.2.2 8.2.3 Central Limit Theorem and the Normal Distribution Normal Distribution of Sample Proportions Normal Distribution of Sample Means 155 8.2.4 8.2.5 The Standard Normal Distribution The Empirical Rule [68-95-99 Rule) 158 158 8.3 Confidence Intervals and Margins of Error 156 157 160 8.3.1 Critical Values for Confidence Intervals 160 8.3.2 8.3.3 Reporting the Confidence Interval for a SampleProportion Reporting the Confidence Interval fora Sample Mean 161 162 8.4 Student’s t-Distribution: When You re Not Completely Normal 8.4.1 The t-Distribution’s Role in Inferential Statistics Critical Values of t-Distributions 8.4.2 163 164 165 KeyTerms 166 Chapters Exercises 166 Chapter 9 Hypothesis Tests with One or Two Samples 169 9.1 Role of the Null Hypothesis 170 9.2
Testing Hypotheses with Sample Proportions 171 9.2.1 9.2.2 Testing One Sample Proportion against a Hypothesized Value Testing the Difference between Two Sample Proportions Using Groups 171 9.2.3 9.2.4 Testing the Difference between Two Sample Proportions UsingVariables 174 175 Testing Hypotheses about Proportions with Weighted Data 9.3 Testing Hypotheses with SampleMeans 173 177 9.3.1 Testing One Sample Mean against a Hypothesized Value 9.3.2 Testing the Difference between Two Sample Means Using Groups 177 179 9.3.3 Testing the Difference between Two Sample Means Using Variables 9.3.4 t-Test Variations from Assumptions about Variance 180 9.3.5 Testing Hypotheses about Means with Weighted Data 182 181 KeyTerms 183 Chapter 9 Exercises 184 ix
X A Stata’ Companion to Political Analysis Chapter 10 Chi-Square Test and Analysis of Variance 10.1 The Chi-Square Test of Independence 10.1.1 How the Chi-Square Test Works 10.1.2 Start with Descriptive Cross-Tabulation 187 189 189 191 10.1.3 Calculating the Chi-Square Test Statistic 191 10.1.4 Reporting and Interpreting Results 193 10.1.5 Chi-Square Test with Weighted Data 10.2 Measuring the Strength of Association between Categorical Variables 193 196 10.2.1 Lambda 196 10.2.2 Somers D 197 10.2.3 Cramer’s V 10.3 Chi-Square Test and Measures of Association in Controlled Comparisons 10.3.1 Analyzing an Ordinal-Level Relationship with a Control Variable 198 200 200 10.3.2 Analyzing a Nominal-Level Relationship with a Control Variable land Weighted Observations) 10.4 Analysis of Variance 10.4.1 How ANOVA Works 203 205 206 10.4.2 Single-FactorANOVA 207 10.4.3 Two-Factor ANOVA 208 10.4.4 Stata s F-Distribution Functions 209 Key Terms 210 Chapter 10 Exercises 210 Chapter 11 Correlation and Bivariate Regression 11.1 Correlation Analysis 213 214 11.1.1 Correlation between Two Variables 214 11.1.2 Correlation among More Than Two Variables 215 11.2 Bivariate Regression Analysis 217 11.3 Creating a Scatterplot with a Linear Prediction Line 219 11.4 Correlation and Bivariate RegressionAnalysis with Weighted Data 222 Key Terms 225 Chapter 11 Exercises 225 Chapter 12 Multiple Regression 12.1 Multiple Regression Analysis 229 230 12.1.1 Estimating and Interpreting a Multiple Regression Model 230 12.1.2 Visualizing Multiple Regression with Bubble Plots 231 12.1.3 Obtaining and Interpreting
Beta Coefficients 233 234 12.1.4 Multiple Regression with Weighted Observations 12.2 Regression with Multiple Dummy Variables 12.2.1 Estimating a Regression Model with Multiple Dummy Variables 12.2.2 Changing the Reference Category 12.2.3 Visualizing Regression with Multiple Dummy Variables 12.3 Interaction Effects in Multiple Regression 12.3.1 Estimating a Regression Model with an Interaction Term 12.3.2 Graphing Linear Prediction Lines for Interaction Relationships 235 235 237 238 240 240 243 Key Terms 244 Chapter 12 Exercises 244 Chapter 13 Analyzing Regression Residuals 13.1 Expected Values, Observed Values, and Regression Residuals 249 250 13.1.1 Example from Bivariate Regression Analysis 250 13.1.2 Residuals from Multiple Regression Analysis 252
Detailed Contents 13.2 Squared and Standardized Residuals 13.2.1 Squared Residuals 13.2.2 Standardized Residuals 253 253 254 13.3 Assumptions about Regression Residuals 255 13.4 Analyzing Graphs of Regression Residuals 257 13.4.1 Histogram of Regression Residuals 257 13.4.2 Residual Diagnostic Plots 258 13.5 Testing Regression Assumptions with Residuals 13.5.1 Testing the Assumption That Residuals Are Normally Distributed 13.5.2 Testing the Constant Variance Assumption 13.5.3 Regression Diagnostics for Multiple Regression Analysis 259 259 260 261 13.6 What If You Diagnose Problems with Residuals? 264 Key Terms 265 Chapter 13 Exercises 265 Chapter 14 Logistic Regression 269 14.1 Odds, Logged Odds, and Probabilities 270 14.2 Estimating Logistic Regression Models 271 14.2.1 Logistic Regression with One Independent Variable 14.2.2 Reporting and Interpreting Odds Ratios 14.2.3 Evaluating Model Fit 272 273 274 14.3 Logistic Regression with Multiple Independent Variables 278 14.4 Graphing Predicted Probabilities with One Independent Variable 280 14.4.1 14.4.2 Interval-Level Independent Variable Categorical Independent Variable 14.5 Graphing Predicted Probabilities with Multiple Independent Variables 280 281 284 14.5.1 14.5.2 14.5.3 One Categorical and One Interval-Level Independent Variable 284 Two Categorical Independent Variables 286 Plotting Predicted Probabilities with the atmeans Option 288 14.5.4 Combining the atmeans and over Options 291 Key Terms 293 Chapter 14 Exercises 294 Chapter 15 Doing Your Own Political Analysis 15.1 Doable Research Ideas 299 300 15.1.1 Political
Knowledge and Interest 15.1.2 Self-Interest and Policy Preferences 300 301 15.1.3 Economic Performance and Election Outcomes 301 15.1.4 Electoral Turnout in Comparative Perspective 15.1.5 Correlates of State Policies 15.1.6 Religion and Politics 301 302 302 15.1.7 Race and Politics 303 15.2 Getting Data into Stata 15.2.1 Opening Stata Formatted Datasets 303 303 15.2.2 Importing Microsoft Excel Datasets 304 15.2.3 Using HTML Table Data 308 15.2.4 Entering Data with Stata s Data Editor 15.3 Writing It Up 309 312 15.3.1 The Research Question 313 15.3.2 Previous Research 313 15.3.3 Data, Hypotheses, and Analysis 313 15.3.4 Conclusions and Implications 314 Key Terms 314 Chapter 15 Exercises 315 Xi
* Stata’ Companion to Political Analysis Appendix, Table A-1 - Variables in the Debate Experiment Dataset 317 Appendix, Table A-2 - Variables in the GSS Dataset in Alphabetical Order 319 Appendix, Table A-3 - Variables in the NES Dataset in Alphabetical Order 333 Appendix, Table A-4 - Variables in the States Dataset by Topic 345 Appendix, Table A-5 - Variables in the World Dataset by Topic 351 Glossary 361
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| adam_txt |
BRIEF CONTENTS List of Boxes xiii List of Figures xv List of Tables xix Preface xxi Acknowledgments xxv xxvii Introduction Chapter 1 Using Stata for Data Analysis Chapter 2 Descriptive Statistics 17 Chapters Transforming Variables 37 Chapter 4 Making Comparisons 61 Chapter 5 Graphing Relationships and Describing Patterns 83 Chapter 6 Random Assignment and Sampling 111 Chapter 7 Making Controlled Comparisons 133 Chapters Foundations of Statistical Inference 151 Chapter 9 Hypothesis Tests with One or Two Samples 169 Chapter 10 Chi-Square Test and Analysis of Variance 187 Chapter 11 Correlation and Bivariate Regression 213 Chapter 12 Multiple Regression 229 Chapter 13 Analyzing Regression Residuals 249 Chapter 14 Logistic Regression 269 Chapter 15 Doing Your Own Political Analysis 299 1 Appendix, Table A-1 - Variables in the Debate Experiment Dataset 317 Appendix, Table A-2 - Variables in the GSS Dataset in Alphabetical Order 319 Appendix, Table A-3 - Variables in the NES Dataset in Alphabetical Order 333 Appendix, Table A-4 - Variables in the States Dataset by Topic 345 Appendix, Table A-5 - Variables in the World Dataset by Topic 351 Glossary 361
DETAILED CONTENTS List of Boxes xiii List of Figures xv List of Tables xix Preface xxi Acknowledgments xxv xxvii Introduction Chapter 1 Using Stata for Data Analysis 1.1 General Syntax of Stata Commands 1 2 1.2 Using Stata's Graphical User Interface Effectively 4 1.3 Do-files 4 1.4 Printing Results and Copying Output 8 1.5 Customizing Your Display 11 1.6 Log Files 12 1.7 Getting Help 13 Key Terms 15 Chapter 1 Exercises 15 Chapter 2 Descriptive Statistics 17 2.1 Identifying Levels of Measurement 18 2.2 Describing Nominal Variables 19 2.3 Describing Ordinal Variables 21 2.4 Bar Charts for Nominal and Ordinal Variables 23 2.5 Describing Interval Variables 25 2.6 Histograms for Interval Variables 29 2.7 Obtaining Case-Level Information 31 Key Terms 33 Chapter 2 Exercises 33 Chapters Transforming Variables 37 3.1 Creating Dummy Variables 38 3.2 Applying Mathematical Operators to Variables 42 3.3 Managing Variable Descriptions and Labels 46 3.3.1 Modifying Variable Labels Using Commands 3.3.2 Modifying Variable Labels with Stata’s Variables Manager 46 47 3.4 Collapsing Variables into Simplified Categories 50 3.5 Centering or Standardizing a Numeric Variable 53 3.6 Creating an Additive Index 54 Key Terms 57 Chapter 3 Exercises 57
viii A Stata® Companion to Political Analysis Making Comparisons Chapter 4 4.1 Cross-Tabulation Analysis 61 62 4.1.1 Generating a Cross-Tabulation 4.1.2 Interpreting Cross-Tabulation Analysis 63 64 4.1.3 Cross-Tabulation with Weighted Observations 4.1.4 Visualizing Cross-Tabulation Analysis with Simple Bar Charts 64 66 4.2 Mean Comparison Analysis 4.2.1 Generating a Mean Comparison Table 69 4.2.2 Interpreting Mean Comparison Analysis 4.2.3 Comparing Means with Weighted Observations 70 70 71 4.2.4 Visualizing Mean Comparisons with Box Plots 74 4.3 Making Comparisons with Interval-Level Independent Variables 77 Key Terms 78 Chapter 4 Exercises 78 Chapter 5 Graphing Relationships and Describing Patterns 5.1 Graphs for Binary Dependent Variables 83 85 5.1.1 Simple Bar Charts with Nominal-Level Independent Variables 85 5.1.2 Area Chart with Ordinal-Level Independent Variables 87 5.1.3 Graphs with Interval-Level Independent Variables 88 5.2 Graphs for Nominal-Level Dependent Variables 90 5.2.1 Clustered Bar Charts with Nominal Independent Variables 90 5.2.2 Multiple Line Plots with Ordinal Independent Variables 92 5.2.3 Graphs with Interval-Level Independent Variables 93 5.3 Graphs for Ordinal-Level Dependent Variables 94 5.3.1 Using Bars to Represent Select Values 94 5.3.2 Stacked Bar Chart for an Ordinal-Ordinal Relationship 96 5.3.3 Graphs with Interval-Level Independent Variables 98 5.4 Graphs for Interval-Level Dependent Variables 5.4.1 Plotting Means with Bars or Lines 101 102 5.4.2 Box Plots 102 5.4.3 Scatterplots 103 Key Terms 107 Chapter 5 Exercises 107 Chapter 6 Random
Assignment and Sampling 6.1 Random Assignment 6.1.1 Two Groups with Equal Probability 112 112 6.1.2 Multiple Groups with Varying Probabilities 113 6.1.3 Random Assignment to Predetermined Size Groups 115 6.2 Analyzing the Results of an Experiment 6.3 111 118 6.2.1 Assessing Random Assignment 119 6.2.2 Evaluating the Effect of Treatment 120 Random Sampling 121 6.3.1 Simple Random Samples with Replacement 121 6.3.2 Simple Random Samples without Replacement 6.3.3 Systematic Random Samples 122 122 6.3.4 Clustered and Stratified Random Samples 124 6.4 Selecting Cases for Qualitative Analysis 125 6.4.1 Most Similar Systems 125 6.4.2 Most Different Systems 127 6.5 Analyzing Data Ethically 128 6.5.1 Ethical Issues in Data Analysis 128 6.5.2 Ten Tips for Writing Replication Do-files 129
Detailed Contents Key Terms 130 Chapter 6 Exercises Chapter 7 7.1 Making Controlled Comparisons 130 133 Cross-Tabulation Analysis with a Control Variable 134 7.1.1 Start with a Basic Cross-Tabulation 7.1.2 Controlling for Another Variable 134 135 7.1.3 Interpreting Controlled Cross-Tabulations 137 7.2 Visualizing Controlled Comparisons with Categorical Dependent Variables 139 7.3 Mean Comparison Analysis with a Control Variable 142 7.3.1 Start with a Basic Mean Comparison Table 7.3.2 Adding Control Variables 142 7.3.3 Interpreting a Controlled Mean Comparison 143 142 7.4 Visualizing Controlled Mean Comparisons 143 KeyTerms 146 Chapter 7 Exercises 146 Chapters Foundations of Statistical Inference 151 8.1 Estimating Population Parameters with Simulations 152 8.2 Expected Shape of Sampling Distributions 155 8.2.1 8.2.2 8.2.3 Central Limit Theorem and the Normal Distribution Normal Distribution of Sample Proportions Normal Distribution of Sample Means 155 8.2.4 8.2.5 The Standard Normal Distribution The Empirical Rule [68-95-99 Rule) 158 158 8.3 Confidence Intervals and Margins of Error 156 157 160 8.3.1 Critical Values for Confidence Intervals 160 8.3.2 8.3.3 Reporting the Confidence Interval for a SampleProportion Reporting the Confidence Interval fora Sample Mean 161 162 8.4 Student’s t-Distribution: When You're Not Completely Normal 8.4.1 The t-Distribution’s Role in Inferential Statistics Critical Values of t-Distributions 8.4.2 163 164 165 KeyTerms 166 Chapters Exercises 166 Chapter 9 Hypothesis Tests with One or Two Samples 169 9.1 Role of the Null Hypothesis 170 9.2
Testing Hypotheses with Sample Proportions 171 9.2.1 9.2.2 Testing One Sample Proportion against a Hypothesized Value Testing the Difference between Two Sample Proportions Using Groups 171 9.2.3 9.2.4 Testing the Difference between Two Sample Proportions UsingVariables 174 175 Testing Hypotheses about Proportions with Weighted Data 9.3 Testing Hypotheses with SampleMeans 173 177 9.3.1 Testing One Sample Mean against a Hypothesized Value 9.3.2 Testing the Difference between Two Sample Means Using Groups 177 179 9.3.3 Testing the Difference between Two Sample Means Using Variables 9.3.4 t-Test Variations from Assumptions about Variance 180 9.3.5 Testing Hypotheses about Means with Weighted Data 182 181 KeyTerms 183 Chapter 9 Exercises 184 ix
X A Stata’ Companion to Political Analysis Chapter 10 Chi-Square Test and Analysis of Variance 10.1 The Chi-Square Test of Independence 10.1.1 How the Chi-Square Test Works 10.1.2 Start with Descriptive Cross-Tabulation 187 189 189 191 10.1.3 Calculating the Chi-Square Test Statistic 191 10.1.4 Reporting and Interpreting Results 193 10.1.5 Chi-Square Test with Weighted Data 10.2 Measuring the Strength of Association between Categorical Variables 193 196 10.2.1 Lambda 196 10.2.2 Somers' D 197 10.2.3 Cramer’s V 10.3 Chi-Square Test and Measures of Association in Controlled Comparisons 10.3.1 Analyzing an Ordinal-Level Relationship with a Control Variable 198 200 200 10.3.2 Analyzing a Nominal-Level Relationship with a Control Variable land Weighted Observations) 10.4 Analysis of Variance 10.4.1 How ANOVA Works 203 205 206 10.4.2 Single-FactorANOVA 207 10.4.3 Two-Factor ANOVA 208 10.4.4 Stata's F-Distribution Functions 209 Key Terms 210 Chapter 10 Exercises 210 Chapter 11 Correlation and Bivariate Regression 11.1 Correlation Analysis 213 214 11.1.1 Correlation between Two Variables 214 11.1.2 Correlation among More Than Two Variables 215 11.2 Bivariate Regression Analysis 217 11.3 Creating a Scatterplot with a Linear Prediction Line 219 11.4 Correlation and Bivariate RegressionAnalysis with Weighted Data 222 Key Terms 225 Chapter 11 Exercises 225 Chapter 12 Multiple Regression 12.1 Multiple Regression Analysis 229 230 12.1.1 Estimating and Interpreting a Multiple Regression Model 230 12.1.2 Visualizing Multiple Regression with Bubble Plots 231 12.1.3 Obtaining and Interpreting
Beta Coefficients 233 234 12.1.4 Multiple Regression with Weighted Observations 12.2 Regression with Multiple Dummy Variables 12.2.1 Estimating a Regression Model with Multiple Dummy Variables 12.2.2 Changing the Reference Category 12.2.3 Visualizing Regression with Multiple Dummy Variables 12.3 Interaction Effects in Multiple Regression 12.3.1 Estimating a Regression Model with an Interaction Term 12.3.2 Graphing Linear Prediction Lines for Interaction Relationships 235 235 237 238 240 240 243 Key Terms 244 Chapter 12 Exercises 244 Chapter 13 Analyzing Regression Residuals 13.1 Expected Values, Observed Values, and Regression Residuals 249 250 13.1.1 Example from Bivariate Regression Analysis 250 13.1.2 Residuals from Multiple Regression Analysis 252
Detailed Contents 13.2 Squared and Standardized Residuals 13.2.1 Squared Residuals 13.2.2 Standardized Residuals 253 253 254 13.3 Assumptions about Regression Residuals 255 13.4 Analyzing Graphs of Regression Residuals 257 13.4.1 Histogram of Regression Residuals 257 13.4.2 Residual Diagnostic Plots 258 13.5 Testing Regression Assumptions with Residuals 13.5.1 Testing the Assumption That Residuals Are Normally Distributed 13.5.2 Testing the Constant Variance Assumption 13.5.3 Regression Diagnostics for Multiple Regression Analysis 259 259 260 261 13.6 What If You Diagnose Problems with Residuals? 264 Key Terms 265 Chapter 13 Exercises 265 Chapter 14 Logistic Regression 269 14.1 Odds, Logged Odds, and Probabilities 270 14.2 Estimating Logistic Regression Models 271 14.2.1 Logistic Regression with One Independent Variable 14.2.2 Reporting and Interpreting Odds Ratios 14.2.3 Evaluating Model Fit 272 273 274 14.3 Logistic Regression with Multiple Independent Variables 278 14.4 Graphing Predicted Probabilities with One Independent Variable 280 14.4.1 14.4.2 Interval-Level Independent Variable Categorical Independent Variable 14.5 Graphing Predicted Probabilities with Multiple Independent Variables 280 281 284 14.5.1 14.5.2 14.5.3 One Categorical and One Interval-Level Independent Variable 284 Two Categorical Independent Variables 286 Plotting Predicted Probabilities with the atmeans Option 288 14.5.4 Combining the atmeans and over Options 291 Key Terms 293 Chapter 14 Exercises 294 Chapter 15 Doing Your Own Political Analysis 15.1 Doable Research Ideas 299 300 15.1.1 Political
Knowledge and Interest 15.1.2 Self-Interest and Policy Preferences 300 301 15.1.3 Economic Performance and Election Outcomes 301 15.1.4 Electoral Turnout in Comparative Perspective 15.1.5 Correlates of State Policies 15.1.6 Religion and Politics 301 302 302 15.1.7 Race and Politics 303 15.2 Getting Data into Stata 15.2.1 Opening Stata Formatted Datasets 303 303 15.2.2 Importing Microsoft Excel Datasets 304 15.2.3 Using HTML Table Data 308 15.2.4 Entering Data with Stata's Data Editor 15.3 Writing It Up 309 312 15.3.1 The Research Question 313 15.3.2 Previous Research 313 15.3.3 Data, Hypotheses, and Analysis 313 15.3.4 Conclusions and Implications 314 Key Terms 314 Chapter 15 Exercises 315 Xi
* Stata’ Companion to Political Analysis Appendix, Table A-1 - Variables in the Debate Experiment Dataset 317 Appendix, Table A-2 - Variables in the GSS Dataset in Alphabetical Order 319 Appendix, Table A-3 - Variables in the NES Dataset in Alphabetical Order 333 Appendix, Table A-4 - Variables in the States Dataset by Topic 345 Appendix, Table A-5 - Variables in the World Dataset by Topic 351 Glossary 361 |
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| author | Pollock, Philip H. III |
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| discipline | Informatik Politologie Soziologie Wirtschaftswissenschaften |
| discipline_str_mv | Informatik Politologie Soziologie Wirtschaftswissenschaften |
| edition | Fifth edition |
| format | Book |
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| genre | (DE-588)4151278-9 Einführung gnd-content |
| genre_facet | Einführung |
| id | DE-604.BV049367788 |
| illustrated | Illustrated |
| index_date | 2024-07-03T22:53:39Z |
| indexdate | 2024-07-10T10:02:46Z |
| institution | BVB |
| isbn | 9781071815045 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034627810 |
| oclc_num | 1410705853 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG DE-703 |
| owner_facet | DE-473 DE-BY-UBG DE-703 |
| physical | xxxiv, 365 Seiten Illustrationen, Diagramme 1112 grams |
| publishDate | 2024 |
| publishDateSearch | 2024 |
| publishDateSort | 2024 |
| publisher | SAGE |
| record_format | marc |
| spelling | Pollock, Philip H. III. Verfasser (DE-588)17065592X aut A stata companion to political analysis Philip H. Pollock III, University of Central Florida, Barry C. Edwards, University of Central Florida Fifth edition Los Angeles ; London ; New Dehli ; Singapore ; Washington DC ; Melbourne SAGE [2024] © 2024 xxxiv, 365 Seiten Illustrationen, Diagramme 1112 grams txt rdacontent n rdamedia nc rdacarrier The Fifth Edition of A Stata® Companion to Political Analysis by Philip H. Pollock III and Barry C. Edwards teaches your students statistics by analyzing research-quality data in Stata. It follows the structure of Essentials of Political Analysis with software instructions, explanations of tests, and many exercises for practice Politische Wissenschaft (DE-588)4076229-4 gnd rswk-swf Stata (DE-588)4617285-3 gnd rswk-swf (DE-588)4151278-9 Einführung gnd-content Politische Wissenschaft (DE-588)4076229-4 s Stata (DE-588)4617285-3 s DE-604 Edwards, Barry C. Sonstige (DE-588)1137219858 oth Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034627810&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Pollock, Philip H. III A stata companion to political analysis Politische Wissenschaft (DE-588)4076229-4 gnd Stata (DE-588)4617285-3 gnd |
| subject_GND | (DE-588)4076229-4 (DE-588)4617285-3 (DE-588)4151278-9 |
| title | A stata companion to political analysis |
| title_auth | A stata companion to political analysis |
| title_exact_search | A stata companion to political analysis |
| title_exact_search_txtP | A stata companion to political analysis |
| title_full | A stata companion to political analysis Philip H. Pollock III, University of Central Florida, Barry C. Edwards, University of Central Florida |
| title_fullStr | A stata companion to political analysis Philip H. Pollock III, University of Central Florida, Barry C. Edwards, University of Central Florida |
| title_full_unstemmed | A stata companion to political analysis Philip H. Pollock III, University of Central Florida, Barry C. Edwards, University of Central Florida |
| title_short | A stata companion to political analysis |
| title_sort | a stata companion to political analysis |
| topic | Politische Wissenschaft (DE-588)4076229-4 gnd Stata (DE-588)4617285-3 gnd |
| topic_facet | Politische Wissenschaft Stata Einführung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034627810&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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