The Application of Statistics to Policy Analysis and Management:
An Introduction
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Table of Contents
Part I: Univariate Descriptive Statistics
Chapter 1: Basics for the Study of Statistics
- Empiricism, Inductive Reasoning, and Logical Positivism
- Concerns about Validity and Reliability
- Units of Analysis and Levels of Measurement
- Precision, False Precision, and Rounding
Chapter 2: Introduction to Descriptive Statistics
- How to Create Coding Categories
- Frequency, Proportion, and Percentage Distributions
- Graphs for Qualitative Data
- Graphs for Quantitative Data
- Reporting Statistics to Others
- The Many Different Shapes of Quantitative Data
- Graphical Distortion and Misrepresentation
Chapter 3: Statistics of Central Tendency
- Mode: The “Most Frequent” Point
- Median: The “Split-Half” Point
- Arithmetic Mean: The “Balancing” Point
- Deviations: The Distances of Data from the Arithmetic Mean
- Comparing the Mode, the Median, and the Arithmetic Mean
- Stable and Unstable Descriptive Statistics
- Reporting Statistics of Central Tendency to Others
Chapter 4: Statistics of Variability
- Index of Qualitative Variation
- Variability Statistics of Range
- Variability Statistics of Deviation
- Sum of Squares, Mean Square, and Standard Deviation
- Using the Standard Deviation
- Standard Scores
- Reporting Statistics of Variability to Others
Part II: Bivariate Descriptive Statistics
Chapter 5: Describing Bivariate Connections between Qualitative Data
- The Presentation of Joint Frequency Distributions
- Joint Proportion and Percentage Distributions
- Contrasting Observed and Expected Joint Distributions
- The Chi Square Statistic for Contingency Tables
- Cramer’s V for Contingency Tables with Nominal Data
- Goodman and Kruskal’s G with Ordinal Data
- Reference Guide for Describing Bivariate Connections between Qualitative Data
Chapter 6: Describing Bivariate Connections between Quantitative Data
- Speaking of Bivariate Connections
- Bivariate Statistics for Describing Connections
- Coefficient of Determination
- Nonlinear Bivariate Connections
- Correlation is NOT a Demonstration of Causation
- The Effect of “Outliers” on the Correlation
- Restriction of Range and Lowered Correlations
Chapter 7: Making Predictions with Quantitative Data
- Predictions Using the Arithmetic Mean
- Predictions Using the Standard Deviation
- Predictions Using the Correlation Coefficient
- Initially Constructing an Exact Regression Model
- Testing the Initial Regression Model
- The Reduction of Prediction Errors
- Forecasting to Provide Flexible “Baselines”
Chapter 8: Multiple Correlation and Multiple Regression with Quantitative Data
- Multiple Correlation—Two Uncorrelated Predictors
- Multiple Regression—Two Uncorrelated Predictors
- Graphic Representation of the Regression Plane
- Multiple Correlation—Two Correlated Predictors
- Multiple Regression—Two Correlated Predictors
- Nonlinear Multiple Correlation and Multiple Regression
- The Use of Qualitative Date In Multiple Regression
Part III: Inferential Statistics
Chapter 9: Introduction to Inferential Statistics
- Working with a Sample of the Population
- Sampling Distributions
- Standard Normal Curve
- Sampling Distributions of Percentage Statistics
- Sampling Distributions of Arithmetic Mean Statistics
Chapter 10: “Yes/No” Inference with One Sample
- The Risks of Making Wrong “Yes/No” Inferences
- Procedure for “Yes/No” Inferences: Percentages
- Procedure for “Yes/No” Inferences: Arithmetic Means
- Two-sided versus One-sided Approach for Inference
- The Jargon of “Yes/No” Inferences with One Sample
- Significance Level, Indetection Level, and Difference
Chapter 11: “Yes/No” Inference with Two Samples
- The Risks of Making Wrong “Yes/No” Inferences
- Procedure for “Yes/No” Inferences: Percentages
- Procedure for “Yes/No” Inferences: Arithmetic Means
- Two-sided versus One-sided Approach for Inference
- The Jargon of “Yes/No” Inferences with Two Samples
- Significance Level, Indetection Level, and Difference
Chapter 12: Estimation of a Population Parameter
- Overview of the Method for Estimating Parameters
- Estimating Population Parameters: Percentages
- Estimating Population Parameters: Arithmetic Means
