Meier K.J., Brudney J.L., Bohte J. Applied Statistics for Public and Nonprofit Administration

Cengage Learning, 2011. — 608 p. — 8th ed. — ISBN: 1111342806, 9781111342807.
As the first book ever published for public administration statistics courses, Applied Statistics for Public and Nonprofit Administration makes a difficult subject accessible to students and practitioners of public administration who have little background in statistics or research methods. Steeped in experience and practice, this landmark text remains the first and best in research methods and statistics for students and practitioners in public-and nonprofit-administration. All statistical techniques used by public administration professionals are covered, and all examples in the text relate to public administration and the nonprofit sector. The text avoids jargon and formulae; instead, it uses a step-by-step approach that facilitates student learning.List of Symbols.Foundations of Quantitative Analysis.
Statistics and Public and Nonprofi t Administration.
Measurement.
Research Design.
Descriptive Statistics.
Frequency Distributions.
Measures of Central Tendency.
Measures of Dispersion.
Probability.
Introduction to Probability.
The Normal Probability Distribution.
The Binomial Probability Distribution.
Some Special Probability Distributions.
Inferential Statistics.
Introduction to Inference.
Hypothesis Testing.
Estimating Population Proportions.
Testing the Diff erence between Two Groups.
Analysis of Nominal and Ordinal Data.
Construction and Analysis of Contingency Tables.
Aids for the Interpretation of Contingency Tables.
Statistical Control Table Analysis.
Regression Analysis.
Introduction to Regression Analysis.
The Assumptions of Linear Regression.
Time Series Analysis.
Multiple Regression.
Interrupted Time Series: Program and Policy Analysis.
Regression Output and Data Management.
Special Topics in Quantitative Management.
Performance Measurement Techniques.
Decision Theory.
Annotated Bibliography.
Statistical Tables.Answers to Odd-Numbered Computational Problems.