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Essential Statistics for Public Managers and Policy Analysts

Essential Statistics for Public Managers and Policy Analysts

Fourth Edition
  • Evan Berman - Victoria University of Wellington, New Zealand
  • Xiaohu Wang - City University of Hong Kong, Kowloon, Hong Kong, University of Central Florida, USA
Additional resources:

January 2017 | 368 pages | CQ Press

Known for its brevity and student-friendly approach, Essential Statistics for Public Managers and Policy Analysts remains one of the most popular introductory books on statistics for public policy and public administration students, using carefully selected examples tailored specifically for them. The Fourth Edition continues to offer a conceptual understanding of statistics that can be applied readily to the real-life challenges of public administrators and policy analysts. The book provides examples from the areas of human resources management, organizational behavior, budgeting, and public policy to illustrate how public administrators interact with and analyze data.

The text may be paired with the workbook Exercising Essential Statistics, Fourth Edition to help students apply each statistical technique introduced in the text. Click here to see more information about the workbook. Use bundle ISBN: 978-1-5063-7366-9.

Available with Perusall—an eBook that makes it easier to prepare for class
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Tables, Figures, and Boxes
Statistics Roadmap
Section I: Introduction
Chapter 1 Why Statistics for Public Managers and Policy Analysts?
Chapter Objectives  
Role of Data in Public Management  
Competency and Proficiency  
Ethics in Data Analysis and Research  
Key Terms  
Section II: Research Methods
Chapter 2 Research Design
Chapter Objectives  
Introducing Variables and Their Relationships  
Program Evaluation  
A Bit More: Extending through Quasi-experimental Design  
Key Terms  
Chapter 3 Conceptualization and Measurement
Chapter Objectives  
Measurement Levels and Scales  
Index Variables  
Measurement Validity  
Key Terms  
Chapter 4 Measuring and Managing Performance: Present and Future
Chapter Objectives  
Performance Measurement  
Managing Performance  
Efficiency, Effectiveness, and a Bit More  
Peering Into the Future: Forecasting  
Key Terms  
Chapter 5 Data Collection
Chapter Objectives  
Sources of Data  
Data Input  
Putting It Together  
Key Terms  
Section III: Descriptive Statistics
Chapter 6 Central Tendency
Chapter Objectives  
The Mean  
The Median  
The Mode  
Key Terms  
Appendix 6.1: Using Grouped Data  
Chapter 7 Measures of Dispersion
Chapter Objectives  
Frequency Distributions  
Standard Deviation  
Key Terms  
Appendix 7.1: Boxplots  
Chapter 8 Contingency Tables
Chapter Objectives  
Contingency Tables  
Relationship and Direction  
Pivot Tables  
Key Terms  
Chapter 9 Getting Results
Chapter Objectives  
Analysis of Outputs and Outcomes  
Analysis of Efficiency and Effectiveness  
Analysis of Equity  
Quality-of-Life Analysis  
A Bit of Forecasting, Too  
Some Cautions in Analysis and Presentation  
Key Terms  
Appendix 9.1: Forecasting with Periodic Effects  
Section IV: Inferential Statistics
Chapter 10 Introducing Inference: Estimation from Samples
Chapter Objectives  
From Sample to Population  
Statistical Estimation of Population Parameters  
Key Terms  
Chapter 11 Hypothesis Testing with Chi-Square
Chapter Objectives  
What Is Chi-Square?  
Hypothesis Testing  
The Goodness-of-Fit Test  
A Nonparametric Alternative  
Key Terms  
Appendix 11.1: Rival Hypotheses: Adding a Control Variable  
Appendix 11.2: Some Nonparametric Tests for Specific Situations  
Chapter 12 The T-Test
Chapter Objectives  
T-Tests for Independent Samples  
Two T-Test Variations  
Nonparametric Alternatives to T-Tests  
Key Terms  
Chapter 13 Analysis of Variance (ANOVA)
Chapter Objectives  
Analysis of Variance  
A Nonparametric Alternative  
Key Terms  
Chapter 14 Simple Regression
Chapter Objectives  
Simple Regression  
Pearson’s Correlation Coefficient  
Spearman’s Rank Correlation Coefficient  
Key Terms  
Chapter 15 Multiple Regression
Chapter Objectives  
Model Specification  
A Working Example  
Further Statistics  
Use of Nominal Variables  
Testing Assumptions  
Key Terms  
Section V: Further Statistics
Chapter 16 Logistic and Time Series Regression
Chapter Objectives  
The Logistic Model  
A Working Example  
Time Series in Multiple Regression  
Key Terms  
Chapter 17 Survey of Other Techniques
Chapter Objectives  
Path Analysis  
Statistical Forecasting  
Survival Analysis  
Factor Analysis  
Key Terms  
A: Normal Distribution
B: Chi-Square (c2) Distribution
C: T-Test Distribution
D: Durbin-Watson Distribution
E: F-Test Distribution
About the Authors


Instructor Site

Password-protected Instructor Resources include the following:

  • Sample course syllabi for semester and quarter courses provide suggested models for structuring one’s course.
  • A set of all the graphics from the text, including all of the maps, tables, and figures, in PowerPoint, .pdf, and .jpg formats for class presentations.
  • Microsoft® Word test bank, is available containing multiple choice, true/false, short answer, and essay questions for each chapter. The test bank provides you with a diverse range of pre-written options as well as the opportunity for editing any question and/or inserting your own personalized questions to effectively assess students’ progress and understanding.
  • Editable, chapter-specific Microsoft® PowerPoint® slides offer you complete flexibility in easily creating a multimedia presentation for your course. Highlight essential content and features.
  • And much more!

affordability, conciseness, relevance to professional work.

Mr Gwen Urey
Urban/Regional Planning Dept, Cal State Polytechnic-Pomona
September 10, 2018
Key features
  • New chapter on introducing inference
  • Improved explanations and updated examples
  • Streamlined chapters on advanced techniques
  • Additional new practice data set and exercise questions
  • Learning objectives are provided at the beginning of each chapte
  • Data sets are provided in Excel, SPSS, Stata, SAS, and SYSTAT formats
  • Concepts are explained using simple language rather than arithmetic formulas and calculations to make the statistical concepts and techniques easily understandable and applicable

Sample Materials & Chapters

Chapter 1

Chapter 11

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