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Tables, Figures, and Boxes | p. xii |
Preface | p. xvi |
Statistics Roadmap | p. xx |
Introduction | p. 1 |
Why Statistics for Public Managers and Analysts? | p. 4 |
Chapter Objectives | p. 4 |
Role of Data in Public Management | p. 4 |
Competency and Proficiency | p. 6 |
Ethics in Data Analysis and Research | p. 10 |
Summary | p. 14 |
Key Terms | p. 15 |
Research Methods | p. 17 |
Research Design | p. 21 |
Chapter Objectives | p. 21 |
Introducing Variables and Their Relationships | p. 21 |
Program Evaluation | p. 26 |
Six Steps | p. 28 |
Rival Hypotheses and Limitations of Experimental Study Designs | p. 30 |
Quasi-Experimental Designs in Program Evaluation | p. 32 |
Summary | p. 39 |
Key Terms | p. 40 |
Conceptualization and Measurement | p. 43 |
Chapter Objectives | p. 43 |
Measurement Levels and Scales | p. 43 |
Conceptualization | p. 48 |
Operationalization | p. 50 |
Index Variables | p. 53 |
Measurement Validity | p. 55 |
Summary | p. 57 |
Key Terms | p. 58 |
Measuring and Managing Performance: Present and Future | p. 61 |
Chapter Objectives | p. 61 |
Performance Measurement | p. 62 |
The Logic Model | p. 63 |
Further Examples | p. 67 |
Efficiency, Effectiveness, and a Bit More | p. 69 |
Managing Performance | p. 73 |
Peering into the Future: Forecasting | p. 75 |
Summary | p. 78 |
Key Terms | p. 78 |
Data Collection | p. 80 |
Chapter Objectives | p. 80 |
Sources of Data | p. 81 |
Administrative Data | p. 81 |
Secondary Data | p. 83 |
Surveys | p. 85 |
Other Sources | p. 89 |
Sampling | p. 90 |
When Is a Sample Needed? | p. 90 |
How Should Samples Be Selected? | p. 91 |
How Large Should the Sample Be? | p. 92 |
Data Input | p. 94 |
Putting It Together | p. 98 |
Summary | p. 100 |
Key Terms | p. 101 |
Descriptive Statistics | p. 103 |
Central Tendency | p. 105 |
Chapter Objectives | p. 105 |
The Mean | p. 106 |
The Median | p. 109 |
The Mode | p. 112 |
Summary | p. 112 |
Key Terms | p. 113 |
Appendix 6.1: Using Grouped Data | p. 113 |
Measures of Dispersion | p. 117 |
Chapter Objectives | p. 117 |
Frequency Distributions | p. 118 |
Standard Deviation | p. 122 |
Definition | p. 122 |
Some Applications of Standard Deviation | p. 124 |
Summary | p. 128 |
Key Terms | p. 129 |
Appendix 7.1: Boxplots | p. 129 |
Contingency Tables | p. 134 |
Chapter Objectives | p. 134 |
Contingency Tables | p. 135 |
Relationship and Direction | p. 138 |
Pivot Tables | p. 141 |
Summary | p. 144 |
Key Terms | p. 146 |
Getting Results | p. 148 |
Chapter Objectives | p. 148 |
Analysis of Outputs and Outcomes | p. 149 |
Analysis of Efficiency and Effectiveness | p. 152 |
Analysis of Equity | p. 154 |
Quality-of-Life Analysis | p. 155 |
Some Cautions in Analysis and Presentation | p. 157 |
The Use of Multiple Measures | p. 157 |
Treatment of Missing Values | p. 159 |
Summary | p. 161 |
Key Terms | p. 162 |
Inferential Statistics | p. 163 |
Hypothesis Testing with Chi-Square | p. 166 |
Chapter Objectives | p. 166 |
What Is Chi-Square? | p. 167 |
Hypothesis Testing | p. 169 |
The Null Hypothesis | p. 170 |
Statistical Significance | p. 171 |
The Five Steps of Hypothesis Testing | p. 174 |
Chi-Square Test Assumptions | p. 177 |
Statistical Significance and Sample Size | p. 178 |
A Nonparametric Alternative | p. 181 |
Summary | p. 182 |
Key Terms | p. 183 |
Appendix 10.1: Rival Hypotheses: Adding a Control Variable | p. 183 |
Measures of Association | p. 188 |
Chapter Objectives | p. 188 |
Three New Concepts | p. 189 |
PRE: The Strength of Relationships | p. 189 |
Paired Cases: The Direction of Relationships | p. 190 |
Dependent Samples | p. 191 |
PRE Alternatives to Chi-Square | p. 192 |
Beating the Standard? The Goodness-of-Fit Test | p. 195 |
Discrimination and Other Tests | p. 197 |
Do the Evaluators Agree? | p. 199 |
Summary | p. 201 |
Key Terms | p. 202 |
The T-Test | p. 205 |
Chapter Objectives | p. 205 |
T-Tests for Independent Samples | p. 206 |
T-Test Assumptions | p. 208 |
Working Example 1 | p. 212 |
Working Example 2 | p. 214 |
Two T-Test Variations | p. 217 |
Paired-Samples T-Test | p. 217 |
One-Sample T-Test | p. 218 |
Nonparametric Alternatives to T-Tests | p. 219 |
Summary | p. 221 |
Key Terms | p. 222 |
Analysis of Variance (ANOVA) | p. 226 |
Chapter Objectives | p. 226 |
Analysis of Variance | p. 227 |
ANOVA Assumptions | p. 229 |
A Working Example | p. 230 |
Beyond One-Way ANOVA | p. 234 |
A Nonparametric Alternative | p. 235 |
Summary | p. 236 |
Key Terms | p. 237 |
Simple Regression | p. 239 |
Chapter Objectives | p. 239 |
Simple Regression | p. 240 |
Scatterplot | p. 240 |
Test of Significance | p. 241 |
Assumptions and Notation | p. 244 |
Pearson's Correlation Coefficient | p. 245 |
Spearman's Rank Correlation Coefficient | p. 256 |
Summary | p. 249 |
Key Terms | p. 249 |
Multiple Regression | p. 252 |
Chapter Objectives | p. 252 |
Model Specification | p. 253 |
A Working Example | p. 256 |
Further Statistics | p. 259 |
Goodness of Fit for Multiple Regression | p. 259 |
Standardized Coefficients | p. 259 |
F-Test | p. 260 |
Use of Nominal variables | p. 261 |
Testing Assumptions | p. 263 |
Outliers | p. 263 |
Multicollinearity | p. 265 |
Linearity | p. 266 |
Heteroscedasticity | p. 267 |
Autocorrelation | p. 268 |
Measurement and Specification | p. 270 |
Summary | p. 273 |
Key Terms | p. 273 |
Further Statistics | p. 277 |
Logistic Regression | p. 279 |
Chapter Objectives | p. 279 |
The Logistic Model | p. 280 |
A Working Example | p. 281 |
Calculating Event Probabilities | p. 283 |
Summary | p. 286 |
Key Terms | p. 286 |
Time Series Analysis | p. 287 |
Chapter Objectives | p. 287 |
Time Series Data in Multiple Regression | p. 288 |
Autocorrelation | p. 288 |
Correcting Autocorrelation | p. 290 |
Policy Evaluation | p. 291 |
Lagged Variables | p. 293 |
Statistical Forecasting Methods: A Primer | p. 294 |
Regression-Based Forecasting | p. 297 |
Forecasting with Leading Indicators | p. 298 |
Curve Estimation | p. 298 |
Exponential Smoothing | p. 299 |
ARIMA | p. 300 |
Non-Regression-Based Forecasting with Few Observations | p. 301 |
Forecasting with Periodic Effects | p. 304 |
Summary | p. 306 |
Key Terms | p. 306 |
Survey of Other Techniques | p. 309 |
Chapter Objectives | p. 309 |
Path Analysis | p. 309 |
Beyond Path Analysis | p. 313 |
Survival Analysis | p. 314 |
Beyond Life Tables | p. 315 |
Factor Analysis | p. 316 |
Beyond Factor Analysis | p. 317 |
Summary | p. 320 |
Key Terms | p. 320 |
Appendix: Statistical Tables | p. 323 |
Normal Distribution | p. 324 |
Chi-Square Distribution | p. 325 |
T-Test Distribution | p. 326 |
Durbin-Watson Distribution | p. 328 |
F-Test Distribution | p. 329 |
Glossary | p. 333 |
Index | p. 349 |
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