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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