Essential Statistics for Public Managers and Policy Analysts / Edition 1

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Overview

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.

CD-ROM includes:

  • 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.
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Product Details

  • ISBN-13: 9781568026473
  • Publisher: Congressional Quarterly, Inc.
  • Publication date: 9/1/2001
  • Edition description: Older Edition
  • Edition number: 1
  • Pages: 195

Table of Contents

Preface xv
Statistics Roadmap xx
Introduction xxiii
Chapter 1 Why Research? An Introduction 1
Chapter Objectives 1
Research Design 3
Six Steps 3
Relationships 5
Rival Hypotheses and Limitations of Experimental Study Designs 8
Measurement and Sampling 11
Measuring Concepts 11
Measuring Variables: Levels and Scales 12
Measuring Variables: Sampling 16
Data Collection 18
Administrative Data 18
Surveys 19
Other Data Sources 20
Putting It Together 21
Conclusion 23
Key Terms 24
Notes 24
Chapter 2 Univariate Analysis: Description 27
Chapter Objectives 27
Measures of Central Tendency 29
The Mean 29
The Median 30
The Mode 32
Using Grouped Data 33
Measures of Dispersion 35
Boxplots 35
Frequency Distributions 38
Standard Deviation 40
Conclusion 45
Key Terms 45
Notes 46
Chapter 3 Hypothesis Testing With Chi-Square 49
Chapter Objectives 49
Contingency Tables 50
Chi-Square 51
Hypothesis Testing 53
The Null Hypothesis 55
Statistical Significance 56
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
Conclusion 67
Key Terms 69
Notes 69
Chapter 4 Measures of Association 71
Chapter Objectives 71
Proportional Reduction in Error 72
Calculating PRE 72
Paired Cases 73
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
Evaluating Rankings 80
Equivalency of Two Samples 83
Statistics for Two Ordinal Variables 84
Conclusion 87
Key Terms 88
Notes 88
Chapter 5 T-Tests and Anova 93
Chapter Objectives 93
Creating Index Variables 94
T-Tests 96
T-Test Assumptions 98
A Working Example 101
Analysis of Variance 104
ANOVA Assumptions 108
A Working Example 108
Conclusion 111
Key Terms 112
Notes 113
Chapter 6 Regression I: Estimation 117
Chapter Objectives 117
Simple Regression 118
Scatterplot 119
Test of Significance 119
Goodness of Fit 121
Assumptions and Notation 123
Multiple Regression 124
Model Specification 124
A Working Example 126
Goodness of Fit for Multiple Regression 128
Standardized Coefficients 128
F-Test 129
Use of Nominal Variables 129
Conclusion 131
Key Terms 132
Notes 132
Chapter 7 Regression II: Assumptions, Time Series 135
Chapter Objectives 135
Testing Assumptions 136
Outliers 136
Multicollinearity 137
Linearity 139
Heteroscedasticity 140
Measurement and Specification 142
Time Series Analysis 145
Detecting Autocorrelation 145
Correcting Autocorrelation 146
Policy Evaluation 148
Lagged Variables 150
Forecasting 151
Forecasting with Few Observations 152
Forecasting with Periodic Effects 155
Conclusion 157
Key Terms 157
Notes 158
Chapter 8 Advanced Statistics 159
Chapter Objectives 159
Logistic Regression 160
Path Analysis 163
Survival Analysis 166
Regression-Based Forecasting 167
Forecasting with Leading Indicators 168
Curve Estimation 168
Exponential Smoothing 169
ARIMA 171
Precis of Other Techniques 171
Beyond Logistic Regression 172
Exploratory Analysis 172
Beyond Life Tables 173
Beyond One-Way ANOVA 173
Beyond Path Analysis 174
Conclusion 174
Key Terms 175
Notes 175
Appendix Statistical Tables 177
Normal Distribution 178
Chi-square Distribution 179
T-test Distribution 180
F-test Distribution 181
Durbin-Watson Distribution 185
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