Essential Statistics for Public Managers and Policy Analysts / Edition 3 available in Paperback
This tightly integrated set -- textbook, workbook and CD-ROM, all blended seamlessly -- presents the basic analytics tools utilized by today's public managers and policy analysts. Tailored specifically to the needs of students in public administration and public policy programs, Essential Statistics introduces and reinforces important statistical skills that will be immediately relevant to them.
Essential Statistics includes:
- clear and concise discussions of statistical concepts and applications, from basic descriptive techniques to more advanced analytical tools.
- learning objectives and key term lists that frame each chapter for quick and easy reference.
- multiple tables, figures, and boxes to reinforce important concepts and enhance skill acquisition.
Exercising Essential Statistics includes:
- critical thinking questions, data-based and research in practice exercises, helpful tips on data presentation, and suggested reading lists that correspond with coverage of each textbook chapter.
- two software guides -- "How to Use SPSS" and "Guide to Using Spreadsheets" -- that capitalize on the increased value of computers in methods courses. Freeing students from time-consuming calculations, these real-world applications allow for quick results interpretation and data validation.
- perforated and spiral-bound pages for maximum flexibility.
- six SPSS data sets that cover a range of measures and applications from citizen and employee survey data, to time series data of juvenile crimes, to an assessment of watersheds developed by the EPA, to regression analysis of pollution, productivity improvement, and crime.
- Eleven spreadsheets that highlight practical ways to conduct data analysis with Excel.
- Data sets in alternate formats -- SAS, SYSTAT, and STATA -- to help expose your students to a range of statistical software packages.
|Edition description:||Third Edition|
|Product dimensions:||6.00(w) x 8.90(h) x 0.70(d)|
About the Author
Evan M. Berman is Professor of Public Management and Director of Internationalization at Victoria University of Wellington, School of Government. Prior, he was the Huey Mc Elveen Distinguished Professor at Louisiana State University. His areas of expertise are human resource management, public performance, local government, and public governance in Asia. He is past Chair of the American Society for Public Administration’s Section of Personnel and Labor Relations. He has over 125 publications and 12 books, including People Skills At Work (CRC Press, 2011), Essential Statistics for Public Managers and Policy Analysts, Third Edition (CQ Press, 2012), and a trilogy of books on Public Administration in Asia (2010, 2011, 2013, CRC Press). He has published in all major journals of the discipline, is Senior Editor of Public Performance & Management Review, a Distinguished Fulbright Scholar, past University Chair Professor at National Chengchi University (Taipei, Taiwan), and a former policy analyst with the National Science Foundation.
Table of Contents
|Chapter 1||Why Research? An Introduction||1|
|Rival Hypotheses and Limitations of Experimental Study Designs||8|
|Measurement and Sampling||11|
|Measuring Variables: Levels and Scales||12|
|Measuring Variables: Sampling||16|
|Other Data Sources||20|
|Putting It Together||21|
|Chapter 2||Univariate Analysis: Description||27|
|Measures of Central Tendency||29|
|Using Grouped Data||33|
|Measures of Dispersion||35|
|Chapter 3||Hypothesis Testing With Chi-Square||49|
|The Null Hypothesis||55|
|The Five Steps of Hypothesis Testing||57|
|Chi-Square Test Assumptions||59|
|Statistical Significance and Sample Size||60|
|A Useful Digression: The Goodness-of-Fit Test||62|
|The Practical Significance of Relationships||64|
|Rival Hypotheses: Adding a Control Variable||66|
|Chapter 4||Measures of Association||71|
|Proportional Reduction in Error||72|
|Statistics for Two Nominal Variables||74|
|Two Nominal Variables||75|
|The Problem of Dependent Samples||77|
|Small Sample Tests for Two-By-Two Tables||78|
|Statistics for Mixed Ordinal-Nominal Data||80|
|Equivalency of Two Samples||83|
|Statistics for Two Ordinal Variables||84|
|Chapter 5||T-Tests and Anova||93|
|Creating Index Variables||94|
|A Working Example||101|
|Analysis of Variance||104|
|A Working Example||108|
|Chapter 6||Regression I: Estimation||117|
|Test of Significance||119|
|Goodness of Fit||121|
|Assumptions and Notation||123|
|A Working Example||126|
|Goodness of Fit for Multiple Regression||128|
|Use of Nominal Variables||129|
|Chapter 7||Regression II: Assumptions, Time Series||135|
|Measurement and Specification||142|
|Time Series Analysis||145|
|Forecasting with Few Observations||152|
|Forecasting with Periodic Effects||155|
|Chapter 8||Advanced Statistics||159|
|Forecasting with Leading Indicators||168|
|Precis of Other Techniques||171|
|Beyond Logistic Regression||172|
|Beyond Life Tables||173|
|Beyond One-Way ANOVA||173|
|Beyond Path Analysis||174|
Most Helpful Customer Reviews
Puts a lot of the topics into language that is understandable.