Essential Statistics for Public Managers and Policy Analysts

ISBN-10: 1608716775
ISBN-13: 9781608716777
Edition: 3rd 2012 (Revised)
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Description: 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,  More...

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Book details

List price: $61.00
Edition: 3rd
Copyright year: 2012
Publisher: CQ Press
Publication date: 1/31/2012
Binding: Paperback
Pages: 392
Size: 6.25" wide x 9.25" long x 0.75" tall
Weight: 1.342
Language: English

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.

Evan M. Berman is Distinguished University Professor at National Chengchi University in Taipei (Taiwan). He is also the Editor-in-Chief of ASPA Book Series in Public Administration & Public Policy (Taylor & Francis), Senior Editor of Public Performance & Management Review and a Distinguished Fulbright Scholar. His areas of expertise are human resource management, public performance, and local government, and international interests have now taken him to Asia. He has over 100 publications and 10 books, including Public Administration in East Asia: Mainland China, Japan, South Korea, Taiwan (CRC Press, 2010), People Skills At Work (CRC Press, 2011, with Dira Berman), Encyclopedia of Public Administration and Public Policy, Third Edition (Taylor & Francis, 2007), and Essential Statistics for Public Managers and Policy Analysts, Second Edition (CQ Press, 2006). He is past Chair of the American Society for Public Administration's Section of Personnel and Labor Relations, and also a former policy analyst with the National Science Foundation. He was previously the Huey McElveen Distinguished Professor at Louisiana State University, and has assisted local jurisdictions on matters of team building, strategic planning, and citizen participation.

Tables, Figures, and Boxes
Preface
Statistics Roadmap
Introduction
Why Statistics for Public Managers and Analysts?
Chapter Objectives
Role of Data in Public Management
Competency and Proficiency
Ethics in Data Analysis and Research
Summary
Key Terms
Research Methods
Research Design
Chapter Objectives
Introducing Variables and Their Relationships
Program Evaluation
Six Steps
Rival Hypotheses and Limitations of Experimental Study Designs
Quasi-Experimental Designs in Program Evaluation
Summary
Key Terms
Conceptualization and Measurement
Chapter Objectives
Measurement Levels and Scales
Conceptualization
Operationalization
Index Variables
Measurement Validity
Summary
Key Terms
Measuring and Managing Performance: Present and Future
Chapter Objectives
Performance Measurement
The Logic Model
Further Examples
Efficiency, Effectiveness, and a Bit More
Managing Performance
Peering into the Future: Forecasting
Summary
Key Terms
Data Collection
Chapter Objectives
Sources of Data
Administrative Data
Secondary Data
Surveys
Other Sources
Sampling
When Is a Sample Needed?
How Should Samples Be Selected?
How Large Should the Sample Be?
Data Input
Putting It Together
Summary
Key Terms
Descriptive Statistics
Central Tendency
Chapter Objectives
The Mean
The Median
The Mode
Summary
Key Terms
Appendix 6.1: Using Grouped Data
Measures of Dispersion
Chapter Objectives
Frequency Distributions
Standard Deviation
Definition
Some Applications of Standard Deviation
Summary
Key Terms
Appendix 7.1: Boxplots
Contingency Tables
Chapter Objectives
Contingency Tables
Relationship and Direction
Pivot Tables
Summary
Key Terms
Getting Results
Chapter Objectives
Analysis of Outputs and Outcomes
Analysis of Efficiency and Effectiveness
Analysis of Equity
Quality-of-Life Analysis
Some Cautions in Analysis and Presentation
The Use of Multiple Measures
Treatment of Missing Values
Summary
Key Terms
Inferential Statistics
Hypothesis Testing with Chi-Square
Chapter Objectives
What Is Chi-Square?
Hypothesis Testing
The Null Hypothesis
Statistical Significance
The Five Steps of Hypothesis Testing
Chi-Square Test Assumptions
Statistical Significance and Sample Size
A Nonparametric Alternative
Summary
Key Terms
Appendix 10.1: Rival Hypotheses: Adding a Control Variable
Measures of Association
Chapter Objectives
Three New Concepts
PRE: The Strength of Relationships
Paired Cases: The Direction of Relationships
Dependent Samples
PRE Alternatives to Chi-Square
Beating the Standard? The Goodness-of-Fit Test
Discrimination and Other Tests
Do the Evaluators Agree?
Summary
Key Terms
The T-Test
Chapter Objectives
T-Tests for Independent Samples
T-Test Assumptions
Working Example 1
Working Example 2
Two T-Test Variations
Paired-Samples T-Test
One-Sample T-Test
Nonparametric Alternatives to T-Tests
Summary
Key Terms
Analysis of Variance (ANOVA)
Chapter Objectives
Analysis of Variance
ANOVA Assumptions
A Working Example
Beyond One-Way ANOVA
A Nonparametric Alternative
Summary
Key Terms
Simple Regression
Chapter Objectives
Simple Regression
Scatterplot
Test of Significance
Assumptions and Notation
Pearson's Correlation Coefficient
Spearman's Rank Correlation Coefficient
Summary
Key Terms
Multiple Regression
Chapter Objectives
Model Specification
A Working Example
Further Statistics
Goodness of Fit for Multiple Regression
Standardized Coefficients
F-Test
Use of Nominal variables
Testing Assumptions
Outliers
Multicollinearity
Linearity
Heteroscedasticity
Autocorrelation
Measurement and Specification
Summary
Key Terms
Further Statistics
Logistic Regression
Chapter Objectives
The Logistic Model
A Working Example
Calculating Event Probabilities
Summary
Key Terms
Time Series Analysis
Chapter Objectives
Time Series Data in Multiple Regression
Autocorrelation
Correcting Autocorrelation
Policy Evaluation
Lagged Variables
Statistical Forecasting Methods: A Primer
Regression-Based Forecasting
Forecasting with Leading Indicators
Curve Estimation
Exponential Smoothing
ARIMA
Non-Regression-Based Forecasting with Few Observations
Forecasting with Periodic Effects
Summary
Key Terms
Survey of Other Techniques
Chapter Objectives
Path Analysis
Beyond Path Analysis
Survival Analysis
Beyond Life Tables
Factor Analysis
Beyond Factor Analysis
Summary
Key Terms
Appendix: Statistical Tables
Normal Distribution
Chi-Square Distribution
T-Test Distribution
Durbin-Watson Distribution
F-Test Distribution
Glossary
Index

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