Applied Statistics for Public Administration

by Meier, Kenneth J.; Brudney, Jeffrey L.

• ISBN13: 9780534195908
• ISBN10: 0534195903
• Edition: 3rd
• Format: Paperback
• Copyright: 1993-01-01
• Publisher: Wadsworth Publishing

Summary

In its first edition, this was the first textbook to be published for methods/statistics courses in Public Administration. Today, Meier and Brudney continue to combine accessibility with an applied approach to presenting research methods. This proven text quickly and easily teaches aspiring public administrators the statistical techniques and methods required in the field.

Author Biography

Kenneth J. Meier (Ph.D., Syracuse University) is currently the Charles Puryear Professor of Liberal Arts, professor of political science, and coordinator of the Programs in American Politics and Public Policy and Administration at Texas AandM University Jeffrey L. Brudney is a professor of political science and director of the Doctor of Public Administration (DPA) program at the University of Georgia

Table of Contents

Preface	p. ix
List of Symbols	p. xxiii
Foundations of Quantitative Analysis	p. 1
Statistics and Public Administration	p. 3
The Advantages of a Statistical Approach	p. 3
Statistics and Options for Managers	p. 5
The Role of Calculation	p. 6
NASPAA Standards for Professional Master's Degree Programs in Public Affairs, Policy, and Administration	p. 7
A Road Map for This Book	p. 8
Measurement	p. 13
Theory of Measurement	p. 14
Measurement Validity	p. 15
Measurement Reliability	p. 17
Increasing Reliability	p. 17
Measuring Reliability	p. 18
Types of Measures	p. 19
Levels of Measurement	p. 20
Chapter Summary	p. 23
Problems	p. 24
Research Design	p. 25
Constructing Causal Explanations	p. 27
Causal Relationships	p. 32
Research Design	p. 35
Experimental Designs of Research	p. 37
Internal Validity	p. 37
External Validity	p. 40
Quasi-Experimental Designs of Research	p. 41
Internal Validity	p. 41
External Validity	p. 44
Research Designs and Validity	p. 45
Chapter Summary	p. 45
Problems	p. 46
Descriptive Statistics	p. 47
Frequency Distributions	p. 49
Constructing a Frequency Distribution	p. 50
The Percentage Distribution	p. 52
Cumulative Frequency Distributions	p. 53
Graphic Presentations	p. 55
Chapter Summary	p. 61
Problems	p. 62
Measures of Central Tendency	p. 67
The Mean	p. 68
The Median	p. 69
The Mode	p. 71
Means for Grouped Data	p. 73
Medians for Grouped Data	p. 76
Modes for Grouped Data	p. 78
The Mean versus the Median	p. 78
Levels of Measurement and Measures of Central Tendency	p. 78
Hierarchy of Measurement	p. 82
Some Cautions	p. 83
Chapter Summary	p. 84
Problems	p. 85
Measures of Dispersion	p. 91
The Standard Deviation	p. 92
Standard Deviations for Grouped Data	p. 95
Shape of a Frequency Distribution	p. 97
Chapter Summary	p. 100
Problems	p. 100
Probability	p. 105
Introduction to Probability	p. 107
Basic Concepts in Probability	p. 107
An Application to Game Theory	p. 111
Introduction to Probability Logic	p. 114
General Rules of Probability	p. 115
The General Rule of Addition	p. 115
The General Rule of Multiplication	p. 118
Chapter Summary	p. 120
Problems	p. 120
The Normal Probability Distribution	p. 125
Characteristics of the Normal Distribution	p. 125
z Scores and the Normal Distribution Table	p. 128
Applications to Public Management	p. 132
A Measurement Technique Based on Standard Normal Scores	p. 137
Chapter Summary	p. 140
Problems	p. 141
The Binomial Probability Distribution	p. 145
Binomial Probabilities	p. 145
The Normal Curve and the Binomial Distribution	p. 151
When to Use the Normal Curve	p. 152
Chapter Summary	p. 152
Problems	p. 153
Some Special Probability Distributions	p. 157
The Hypergeometric Probability Distribution	p. 157
The Poisson Distribution	p. 159
The Exponential Probability Distribution	p. 162
Chapter Summary	p. 162
Problems	p. 162
Inferential Statistics	p. 165
Introduction to Inference	p. 167
Some Definitions	p. 168
Estimating a Population Mean	p. 169
Estimating a Population Standard Deviation	p. 170
The Standard Error	p. 170
An Example	p. 172
Chapter Summary	p. 174
Problems	p. 175
Hypothesis Testing	p. 179
Steps in Hypothesis Testing	p. 180
Testing Hypotheses with Population Parameters	p. 181
Hypothesis Testing with Samples	p. 182
How Sure Should a Person Be?	p. 183
One- and Two-Tailed Tests	p. 184
Errors	p. 186
Determining Sample Size	p. 187
Chapter Summary	p. 189
Problems	p. 189
Estimating Population Proportions	p. 193
Estimating a Population Proportion	p. 193
Proportions	p. 195
A Digression	p. 196
Determining Sample Size	p. 197
Decision Making	p. 198
Chapter Summary	p. 199
Problems	p. 199
Testing the Difference Between Two Groups	p. 201
Difference of Means Procedure	p. 201
Other Differences of Means Tests	p. 203
Proportions	p. 206
Chapter Summary	p. 208
Problems	p. 208
Analysis of Nominal and Ordinal Data	p. 215
Construction and Analysis of Contingency Tables	p. 217
Percentage Distributions	p. 218
Steps in Percentaging	p. 219
Displaying and Interpreting Percentage Distributions	p. 220
Collapsing Percentage Distributions	p. 221
Contingency Table Analysis	p. 223
Constructing Contingency Tables	p. 223
Relationships Between Variables	p. 224
Example: Automobile Maintenance in Berrysville	p. 227
Larger Contingency Tables	p. 229
Displaying Contingency Tables	p. 230
Chapter Summary	p. 232
Problems	p. 232
Aids for the Interpretation of Contingency Tables	p. 237
The Chi-Square Test: Statistical Significance for Constituency Tables	p. 238
Example: Incompetence in the Federal Government?	p. 238
Limitations of the Chi-Square Test	p. 241
Assessing the Strength of a Relationship	p. 243
The Percentage Difference	p. 243
Perfect and Null Relationships	p. 244
Measures of Association	p. 247
An Ordinal Measure of Association: Gamma	p. 248
Other Ordinal Measures of Association: Kendall's tau-b and tau-c and Somers's d[subscript yx] and d[subscript xy]	p. 250
A Nominal Measure of Association: Lambda	p. 252
A Nominal Measure of Association Based on Chi-Square: Cramer's V	p. 254
Use of Nominal Measures of Association with Ordinal Data	p. 255
Measures of Association for Larger Tables	p. 255
Chapter Summary	p. 259
Problems	p. 260
Statistical Control Table Analysis	p. 265
Controlling for a Third Variable	p. 267
Alcoholism in the Postal Service--The Effect of Hierarchical Position	p. 267
Performance on the Civil Service Examination--A Case of Favoritism in Blakely?	p. 271
Race, Education, and Complaints--A Developmental Sequence	p. 276
Guaranteed Annual Income--A Case of Interaction	p. 276
Support for Performance-Based Pay--Evidence of Joint Causation	p. 280
Results and Implications of Control Table Analysis	p. 283
Limitations of the Control Table Technique	p. 285
Multivariate Relationships	p. 285
The Source of Control Variables	p. 285
Chapter Summary	p. 286
Problems	p. 286
Regression Analysis	p. 293
Introduction to Regression Analysis	p. 295
Relationships Between Variables	p. 296
Ode to Eyeballing	p. 300
Linear Regression	p. 304
Some Applications	p. 307
An Example	p. 307
Measure of Goodness to Fit	p. 309
The Standard Error of the Estimate	p. 309
The Coefficient of Determination	p. 312
The Standard Error of the Slope	p. 313
Chapter Summary	p. 315
Problems	p. 316
Answer to Regression Problem	p. 321
The Assumptions of Linear Regression	p. 323
Assumption 1	p. 324
Assumption 2	p. 325
Assumption 3	p. 326
Assumption 4	p. 326
Assumption 5	p. 330
Chapter Summary	p. 333
Problems	p. 333
Time Series Analysis	p. 337
Introduction to Time series	p. 338
Forecasting Without Fluctuation	p. 341
Forecasting an Exponential Trend	p. 344
Forecasting with a Short-Term Fluctuation	p. 348
Bivariate Forecasting	p. 351
Chapter Summary	p. 354
Problems	p. 355
Multiple Regression	p. 361
An Example	p. 361
Calculating Partial Slopes	p. 365
The Logic of Controls	p. 366
A Spurious Relationship	p. 366
A Specification	p. 366
Dummy Variable Regression	p. 367
Regression with Three Independent Variables	p. 368
An Example	p. 368
Calculating Regression Coefficients	p. 369
Testing a Hypothesis	p. 370
Polynomial Curve Fitting	p. 371
Quadratic Relationships	p. 371
Cubic Regression	p. 373
Chapter Summary	p. 375
Problems	p. 376
Interrupted Time Series: Program and Policy Analysis	p. 383
Short-Term Impacts	p. 384
Long-Term Impacts	p. 387
Both Short- and Long-Term Effects	p. 390
Pulse Effects	p. 393
Some Considerations	p. 394
Using Data to Represent Program Changes	p. 395
Controlling for Other Variables	p. 396
Chapter Summary	p. 397
Problems	p. 397
Special Topics in Quantitative Management	p. 401
Decision Theory	p. 403
The Rational Decision-Making Model	p. 403
A Brief Critique	p. 406
Decision Making Under Certainty	p. 406
Decision Making Under Risk	p. 407
The Value of Perfect Information	p. 411
Decision Making Under Risk: Decision Trees	p. 412
Decision Making Under Uncertainty	p. 414
The Bayesian Approach	p. 417
The Insufficient Reason Approach	p. 417
The Maximin Principle	p. 417
Minimax Regret	p. 418
Maximax	p. 419
How to Decide?	p. 419
Game Theory	p. 419
Zero-Sum Games	p. 419
Positive-Sum Games	p. 421
The Prisoner's Dilemma	p. 421
A Final Comment	p. 422
Chapter Summary	p. 423
Problems	p. 423
Linear Programming	p. 427
An Example	p. 428
Linear Programming with More Than Two Variables	p. 433
Chapter Summary	p. 433
Problems	p. 434
Annotated Bibliography	p. 437
Statistical Tables	p. 441
Glossary	p. 451
Answers to Odd-Numbered Computational Problems	p. 461
Index	p. 481
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