The Application of Statistics to Policy Analysis and Management:An Introduction   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