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- ISBN: 9780534195908 | 0534195903
- Cover: Paperback
- Copyright: 1/1/1993
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.
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
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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