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Essential Statistics for Public Managers and Policy Analysts



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Essential Statistics: Known for its brevity and student-friendly approach, this new third edition of Essential Statistics provides students with a strong conceptual foundation, but continues to stress application. Class-tested learning objectives, key term lists, and numeroustables, figures, and charts further enhance skill acquisition. Fully updated, this edition touts: two new chapters on applications in performance management and analysis and ANOVA new coverage of essential nonparametric alternatives to conventional inferential statistics additional material on performance management, going beyond an emphasis on performance measurement.

Table of Contents

Tables, Figures, and Boxesp. xii
Prefacep. xvi
Statistics Roadmapp. xx
Introductionp. 1
Why Statistics for Public Managers and Analysts?p. 4
Chapter Objectivesp. 4
Role of Data in Public Managementp. 4
Competency and Proficiencyp. 6
Ethics in Data Analysis and Researchp. 10
Summaryp. 14
Key Termsp. 15
Research Methodsp. 17
Research Designp. 21
Chapter Objectivesp. 21
Introducing Variables and Their Relationshipsp. 21
Program Evaluationp. 26
Six Stepsp. 28
Rival Hypotheses and Limitations of Experimental Study Designsp. 30
Quasi-Experimental Designs in Program Evaluationp. 32
Summaryp. 39
Key Termsp. 40
Conceptualization and Measurementp. 43
Chapter Objectivesp. 43
Measurement Levels and Scalesp. 43
Conceptualizationp. 48
Operationalizationp. 50
Index Variablesp. 53
Measurement Validityp. 55
Summaryp. 57
Key Termsp. 58
Measuring and Managing Performance: Present and Futurep. 61
Chapter Objectivesp. 61
Performance Measurementp. 62
The Logic Modelp. 63
Further Examplesp. 67
Efficiency, Effectiveness, and a Bit Morep. 69
Managing Performancep. 73
Peering into the Future: Forecastingp. 75
Summaryp. 78
Key Termsp. 78
Data Collectionp. 80
Chapter Objectivesp. 80
Sources of Datap. 81
Administrative Datap. 81
Secondary Datap. 83
Surveysp. 85
Other Sourcesp. 89
Samplingp. 90
When Is a Sample Needed?p. 90
How Should Samples Be Selected?p. 91
How Large Should the Sample Be?p. 92
Data Inputp. 94
Putting It Togetherp. 98
Summaryp. 100
Key Termsp. 101
Descriptive Statisticsp. 103
Central Tendencyp. 105
Chapter Objectivesp. 105
The Meanp. 106
The Medianp. 109
The Modep. 112
Summaryp. 112
Key Termsp. 113
Appendix 6.1: Using Grouped Datap. 113
Measures of Dispersionp. 117
Chapter Objectivesp. 117
Frequency Distributionsp. 118
Standard Deviationp. 122
Definitionp. 122
Some Applications of Standard Deviationp. 124
Summaryp. 128
Key Termsp. 129
Appendix 7.1: Boxplotsp. 129
Contingency Tablesp. 134
Chapter Objectivesp. 134
Contingency Tablesp. 135
Relationship and Directionp. 138
Pivot Tablesp. 141
Summaryp. 144
Key Termsp. 146
Getting Resultsp. 148
Chapter Objectivesp. 148
Analysis of Outputs and Outcomesp. 149
Analysis of Efficiency and Effectivenessp. 152
Analysis of Equityp. 154
Quality-of-Life Analysisp. 155
Some Cautions in Analysis and Presentationp. 157
The Use of Multiple Measuresp. 157
Treatment of Missing Valuesp. 159
Summaryp. 161
Key Termsp. 162
Inferential Statisticsp. 163
Hypothesis Testing with Chi-Squarep. 166
Chapter Objectivesp. 166
What Is Chi-Square?p. 167
Hypothesis Testingp. 169
The Null Hypothesisp. 170
Statistical Significancep. 171
The Five Steps of Hypothesis Testingp. 174
Chi-Square Test Assumptionsp. 177
Statistical Significance and Sample Sizep. 178
A Nonparametric Alternativep. 181
Summaryp. 182
Key Termsp. 183
Appendix 10.1: Rival Hypotheses: Adding a Control Variablep. 183
Measures of Associationp. 188
Chapter Objectivesp. 188
Three New Conceptsp. 189
PRE: The Strength of Relationshipsp. 189
Paired Cases: The Direction of Relationshipsp. 190
Dependent Samplesp. 191
PRE Alternatives to Chi-Squarep. 192
Beating the Standard? The Goodness-of-Fit Testp. 195
Discrimination and Other Testsp. 197
Do the Evaluators Agree?p. 199
Summaryp. 201
Key Termsp. 202
The T-Testp. 205
Chapter Objectivesp. 205
T-Tests for Independent Samplesp. 206
T-Test Assumptionsp. 208
Working Example 1p. 212
Working Example 2p. 214
Two T-Test Variationsp. 217
Paired-Samples T-Testp. 217
One-Sample T-Testp. 218
Nonparametric Alternatives to T-Testsp. 219
Summaryp. 221
Key Termsp. 222
Analysis of Variance (ANOVA)p. 226
Chapter Objectivesp. 226
Analysis of Variancep. 227
ANOVA Assumptionsp. 229
A Working Examplep. 230
Beyond One-Way ANOVAp. 234
A Nonparametric Alternativep. 235
Summaryp. 236
Key Termsp. 237
Simple Regressionp. 239
Chapter Objectivesp. 239
Simple Regressionp. 240
Scatterplotp. 240
Test of Significancep. 241
Assumptions and Notationp. 244
Pearson's Correlation Coefficientp. 245
Spearman's Rank Correlation Coefficientp. 256
Summaryp. 249
Key Termsp. 249
Multiple Regressionp. 252
Chapter Objectivesp. 252
Model Specificationp. 253
A Working Examplep. 256
Further Statisticsp. 259
Goodness of Fit for Multiple Regressionp. 259
Standardized Coefficientsp. 259
F-Testp. 260
Use of Nominal variablesp. 261
Testing Assumptionsp. 263
Outliersp. 263
Multicollinearityp. 265
Linearityp. 266
Heteroscedasticityp. 267
Autocorrelationp. 268
Measurement and Specificationp. 270
Summaryp. 273
Key Termsp. 273
Further Statisticsp. 277
Logistic Regressionp. 279
Chapter Objectivesp. 279
The Logistic Modelp. 280
A Working Examplep. 281
Calculating Event Probabilitiesp. 283
Summaryp. 286
Key Termsp. 286
Time Series Analysisp. 287
Chapter Objectivesp. 287
Time Series Data in Multiple Regressionp. 288
Autocorrelationp. 288
Correcting Autocorrelationp. 290
Policy Evaluationp. 291
Lagged Variablesp. 293
Statistical Forecasting Methods: A Primerp. 294
Regression-Based Forecastingp. 297
Forecasting with Leading Indicatorsp. 298
Curve Estimationp. 298
Exponential Smoothingp. 299
ARIMAp. 300
Non-Regression-Based Forecasting with Few Observationsp. 301
Forecasting with Periodic Effectsp. 304
Summaryp. 306
Key Termsp. 306
Survey of Other Techniquesp. 309
Chapter Objectivesp. 309
Path Analysisp. 309
Beyond Path Analysisp. 313
Survival Analysisp. 314
Beyond Life Tablesp. 315
Factor Analysisp. 316
Beyond Factor Analysisp. 317
Summaryp. 320
Key Termsp. 320
Appendix: Statistical Tablesp. 323
Normal Distributionp. 324
Chi-Square Distributionp. 325
T-Test Distributionp. 326
Durbin-Watson Distributionp. 328
F-Test Distributionp. 329
Glossaryp. 333
Indexp. 349
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