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Applied Statistics for Public and Non-Profit Administration,9780534602680
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Applied Statistics for Public and Non-Profit Administration

by ; ;
Edition:
6th
ISBN13:

9780534602680

ISBN10:
0534602681
Format:
Paperback
Pub. Date:
4/22/2005
Publisher(s):
Cengage Learning
List Price: $281.66
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Summary

Part I: FOUNDATIONS OF QUANTITATIVE ANALYSIS. 1. Statistics and Public Administration and Nonprofit Administration. 2. Measurement. 3. Research Design. Part II: DESCRIPTIVE STATISTICS. 4. Frequency Distributions. 5. Measures of Central Tendency. 6. Measures of Dispersion. Part III: PROBABILITY. 7. Introduction to Probability. 8. The Normal Probability Distribution. 9. The Binomial Probability Distribution. 10. Some Special Probability Distributions. Part IV: INFERENTIAL STATISTICS. 11. Introduction to Inference. 12. Hypothesis Testing. 13. Estimating Population Proportions. 14. Testing the Difference Between Two Groups. Part V: ANALYSIS OF NOMINAL AND ORDINAL DATA. 15. Construction and Analysis of Contingency Tables. 16. Aids for the Interpretation of Contingency Tables. 17. Statistical Control Table Analysis. Part VI: REGRESSION ANALYSIS. 18. Introduction to Regression Analysis. 19. The Assumptions of Linear Regression. 20. Time Series Analysis. 21. Multiple Regression. 22. Interrupted Time Series: Program and Policy Analysis. Part VII: SPECIAL TOPICS IN QUANTITATIVE MANAGEMENT. 23. Regression Output and Data Management. Part VII: SPECIAL TOPICS IN QUANTITATIVE MANAGEMENT. 24. Performance Measurement Techniques. 25. Decision Theory. 26. Linear Programming.

Table of Contents

List of Symbols xix
Preface xxi
Part I Foundations of Quantitative Analysis 1(54)
Chapter 1 Statistics and Public and Nonprofit Administration
3(10)
The Advantages of a Statistical Approach
3(2)
Statistics and Options for Managers
5(1)
The Role of Calculation
6(1)
NASPAA Standards for Professional Master's Degree Programs in Public Affairs, Policy, and Administration
7(1)
A Road Map for This Book
8(5)
Chapter 2 Measurement
13(18)
Theory of Measurement
14(1)
Measurement Validity
15(2)
Measurement Reliability
17(2)
Increasing Reliability
17(1)
Measuring Reliability
18(1)
Types of Measures
19(1)
Levels of Measurement
20(4)
The Implications of Selecting a Particular Level of Measurement
24(2)
Chapter Summary
26(1)
Problems
27(4)
Chapter 3 Research Design
31(24)
Constructing Causal Explanations
33(5)
Causal Relationships
38(3)
Research Design
41(2)
Experimental Designs of Research
43(5)
Internal Validity
43(3)
External Validity
46(2)
Quasi-Experimental Designs of Research
48(3)
Internal Validity
48(2)
External Validity
50(1)
Research Designs and Validity
51(1)
Chapter Summary
52(1)
Problems
52(3)
Part II Descriptive Statistics 55(58)
Chapter 4 Frequency Distributions
57(18)
Constructing a Frequency Distribution
58(2)
The Percentage Distribution
60(1)
Cumulative Frequency Distributions
61(2)
Graphic Presentations
63(6)
Chapter Summary
69(1)
Problems
70(5)
Chapter 5 Measures of Central Tendency
75(24)
The Mean
76(1)
The Median
77(2)
The Mode
79(2)
Means for Grouped Data
81(3)
Medians for Grouped Data
84(2)
Modes for Grouped Data
86(1)
The Mean versus the Median
86(1)
Levels of Measurement and Measures of Central Tendency
86(4)
Hierarchy of Measurement
90(1)
Some Cautions
91(1)
Chapter Summary
92(1)
Problems
93(6)
Chapter 6 Measures of Dispersion
99(14)
The Standard Deviation
100(3)
Standard Deviations for Grouped Data
103(2)
Shape of a Frequency Distribution
105(3)
The Importance of Using Measures of Dispersion and Measures of Central Tendency Together
108(1)
Chapter Summary
109(1)
Problems
109(4)
Part III Probability 113(60)
Chapter 7 Introduction to Probability
115(18)
Basic Concepts in Probability
115(4)
An Application to Game Theory
119(3)
Introduction to Probability Logic
122(1)
General Rules of Probability
123(5)
The General Rule of Addition
123(3)
The General Rule of Multiplication
126(2)
Chapter Summary
128(1)
Problems
128(5)
Chapter 8 The Normal Probability Distribution
133(20)
Characteristics of the Normal Distribution
133(3)
z Scores and the Normal Distribution Table
136(4)
Applications to Public Management
140(5)
A Measurement Technique Based on Standard Normal Scores
145(3)
Chapter Summary
148(1)
Problems
149(4)
Chapter 9 The Binomial Probability Distribution
153(12)
Binomial Probabilities
153(6)
The Normal Curve and the Binomial Distribution
159(1)
When to Use the Normal Curve
160(1)
Chapter Summary
160(1)
Problems
161(4)
Chapter 10 Some Special Probability Distributions
165(8)
The Hypergeometric Probability Distribution
165(2)
The Poisson Distribution
167(3)
The Exponential Probability Distribution
170(1)
Chapter Summary
170(1)
Problems
170(3)
Part IV Inferential Statistics 173(62)
Chapter 11 Introduction to Inference
175(14)
Some Definitions
176(1)
Estimating a Population Mean
177(1)
Estimating a Population Standard Deviation
178(1)
The Standard Error
179(1)
How Sample Size Affects the Standard Error
180(1)
The t Distribution
181(1)
An Example
182(2)
Chapter Summary
184(1)
Problems
185(4)
Chapter 12 Hypothesis Testing
189(20)
Steps in Hypothesis Testing
191(1)
The Importance of Stating the Null and Alternative Hypotheses Correctly
192(1)
Testing Hypotheses with Population Parameters
193(1)
Hypothesis Testing with Samples
194(2)
How Sure Should a Person Be?
196(2)
One- and Two-Tailed Tests
198(2)
Errors
200(1)
Determining Sample Size
201(2)
Chapter Summary
203(1)
Problems
203(3)
Answers to Sample Null and Research Hypotheses
206(3)
Chapter 13 Estimating Population Proportions
209(8)
Estimating a Population Proportion
209(2)
Proportions
211(1)
A Digression
212(1)
Determining Sample Size
213(1)
Decision Making
214(1)
Chapter Summary
215(1)
Problems
215(2)
Chapter 14 Testing the Difference between Two Groups
217(18)
Stating the Research and Null Hypotheses for Difference of Means Tests
217(2)
Difference of Means Procedure
219(2)
Understanding the Three Major Difference of Means Tests
221(1)
t Test Assuming Independent Samples with Unequal Variances
222(2)
t Test Assuming Independent Samples with Equal Variances
224(2)
t Test Assuming Dependent Samples
226(1)
Proportions
227(2)
Chapter Summary
229(1)
Problems
229(6)
Part V Analysis of Nominal and Ordinal Data 235(80)
Chapter 15 Construction and Analysis of Contingency Tables
237(22)
Percentage Distributions
238(5)
Steps in Percentaging
239(1)
Displaying and Interpreting Percentage Distributions
240(1)
Collapsing Percentage Distributions
241(2)
Contingency Table Analysis
243(7)
Constructing Contingency Tables
244(2)
Relationships between Variables
246(3)
Example: Automobile Maintenance in Berrysville
249(1)
Larger Contingency Tables
250(2)
Displaying Contingency Tables
252(1)
Chapter Summary
253(1)
Problems
254(5)
Chapter 16 Aids for the Interpretation of Contingency Tables
259(28)
The Chi-Square Test: Statistical Significance for Contingency Tables
260(5)
Example: Incompetence in the Federal Government?
260(4)
Limitations of the Chi-Square Test
264(1)
Assessing the Strength of a Relationship
265(4)
The Percentage Difference
265(2)
Perfect and Null Relationships
267(2)
Measures of Association
269(4)
An Ordinal Measure of Association: Gamma
270(3)
Other Ordinal Measures of Association: Kendall's tau-b and tau-c and Somers's dyx and dxy
273(3)
A Nominal Measure of Association: Lambda
274(2)
A Nominal Measure of Association Based on Chi-Square: Cramér's V
276(6)
Use of Nominal Measures of Association with Ordinal Data
277(1)
Measures of Association for Larger Tables
278(4)
Chapter Summary
282(1)
Problems
282(5)
Chapter 17 Statistical Control Table Analysis
287(28)
Controlling for a Third Variable
289(16)
Example 1: Alcoholism in the Postal Service
The Effect of Hierarchical Position
289(4)
Example 2: Performance on the Civil Service Examination
A Case of Favoritism in Blakely?
293(5)
Example 2 1/2: Race, Education, and Complaints
A Developmental Sequence
298(1)
Example 3: Guaranteed Annual Income
A Case of Interaction
298(4)
Example 4: Support for Performance-Based Pay
Evidence of Joint Causation
302(3)
Results and Implications of Control Table Analysis
305(2)
Limitations of the Control Table Technique
307(1)
Multivariate Relationships
307(1)
The Source of Control Variables
307(1)
Chapter Summary
308(1)
Problems
308(7)
Part VI Regression Analysis 315(142)
Chapter 18 Introduction to Regression Analysis
317(30)
Relationships between Variables
318(4)
Ode to Eyeballing
322(4)
Linear Regression
326(3)
Some Applications
329(1)
An Example
329(2)
Measures of Goodness of Fit
331(1)
The Standard Error of the Estimate
332(2)
The Coefficient of Determination
334(2)
The Standard Error of the Slope
336(3)
Chapter Summary
339(1)
Problems
339(6)
Answer to Regression Problem
345(2)
Chapter 19 The Assumptions of Linear Regression
347(14)
Assumption 1
348(1)
Assumption 2
349(1)
Assumption 3
350(1)
Assumption 4
350(4)
Assumption 5
354(3)
Chapter Summary
357(1)
Problems
357(4)
Chapter 20 Time Series Analysis
361(24)
Introduction to Time Series
362(3)
Forecasting without Fluctuation
365(3)
Forecasting an Exponential Trend
368(4)
Forecasting with a Short-Term Fluctuation
372(3)
Bivariate Forecasting
375(3)
Chapter Summary
378(1)
Problems
379(6)
Chapter 21 Multiple Regression
385(30)
An Example
386(4)
Calculating Partial Slopes
390(1)
The Logic of Controls
391(1)
A Spurious Relationship
391(1)
A Specification
392(1)
Dummy Variable Regression
392(1)
Regression with Three Independent Variables
393(2)
An Example
393(2)
Calculating Regression Coefficients
395(1)
Testing a Hypothesis
395(1)
Two Additional Regression Assumptions
396(5)
Assumption 1: Model is Specified Correctly
396(3)
Assumption 2: Low Multicollinearity
399(2)
Polynomial Curve Fitting
401(5)
Quadratic Relationships
401(2)
Cubic Regression
403(3)
Chapter Summary
406(1)
Problems
406(9)
Chapter 22 Interrupted Time Series: Program and Policy Analysis
415(20)
Short-Term Impacts
416(3)
Long-Term Impacts
419(3)
Both Short- and Long Term Effects
422(3)
Pulse Effects
425(1)
Some Considerations
426(3)
Using Data to Represent Program Changes
429(1)
Controlling for Other Variables
430(1)
Chapter Summary
431(1)
Problems
431(4)
Chapter 23 Regression Output and Data Management
435(22)
Bivariate Regression Output
435(5)
Example 1
435(3)
Example 2
438(2)
Multiple Regression Output
440(3)
Standardized Coefficients
441(1)
The F Statistic
442(1)
Time Series and Dummy Variable Regression Output
443(3)
Coefficients
443(3)
What to Report When Discussing Regression Output
446(1)
Data Management Issues
447(1)
Managing Variables
447(1)
Missing Values
447(1)
The Importance of Examining Descriptive Statistics Prior to Using More Advanced Statistical Techniques
448(2)
The Range and Other Descriptive Statistics
449(1)
The Importance of Plotting Data before Analysis
449(1)
Chapter Summary
450(1)
Problems
450(7)
Part VII Special Topics in Quantitative Management 457(62)
Chapter 24 Performance Measurement Techniques
459(26)
Defining Inputs, Outputs, and Outcomes
460(4)
Inputs
460(1)
Outputs versus Outcomes
460(2)
Inputs, Outputs, and Efficiency
462(1)
Outcome Measures from External Sources
463(1)
The Importance of Using Multiple Output and Outcome Measures
463(1)
Techniques for Presenting Performance Data
464(3)
Graphical Presentations
465(2)
Trend Analysis
467(8)
Benchmarking
475(2)
Causality Issues in Explaining Performance
477(1)
Chapter Summary
478(1)
Problems
479(6)
Chapter 25 Decision Theory
485(24)
The Rational Decision-Making Model
485(3)
A Brief Critique
488(1)
Decision Making under Certainty
488(1)
Decision Making under Risk
489(4)
The Value of Perfect Information
493(1)
Decision Making under Risk: Decision Trees
494(2)
Decision Making under Uncertainty
496(5)
Strategy 1: The Bayesian Approach
499(1)
Strategy 2: The Insufficient Reason Approach
499(1)
Strategy 3: The Maximin Principle
499(1)
Strategy 4: Minimax Regret
500(1)
Strategy 5: Maximax
501(1)
How to Decide?
501(1)
Game Theory
501(4)
Zero-Sum Games
501(2)
Positive-Sum Games
503(1)
The Prisoner's Dilemma
503(1)
A Final Comment
504(1)
Chapter Summary
505(1)
Problems
505(4)
Chapter 26 Linear Programming
509(10)
An Example
510(5)
Linear Programming with More Than Two Variables
515(1)
Chapter Summary
515(1)
Problems
516(3)
Annotated Bibliography 519(6)
Statistical Tables 525(10)
Glossary 535(12)
Answers to Odd-Numbered Computational Problems 547(23)
Index 570


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