Practical Data Analysis with JMP, Third Edition. Robert Carver
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Chapter 4: Describing Two Variables at a Time
Describing Covariation: Two Categorical Variables
Describing Covariation: One Continuous, One Categorical Variable
Describing Covariation: Two Continuous Variables
Chapter 5: Review of Descriptive Statistics
The World Development Indicators
Applying an Analytic Framework
Preparation for Analysis
Univariate Descriptions
Explore Relationships with Graph Builder
Further Analysis with the Multivariate Platform
Further Analysis with Fit Y by X
Summing Up: Interpretation and Conclusions
Visualizing Multiple Relationships
Chapter 6: Elementary Probability and Discrete Distributions
Overview
The Role of Probability in Data Analysis
Elements of Probability Theory
Contingency Tables and Probability
Discrete Random Variables: From Events to Numbers
Three Common Discrete Distributions
Simulating Random Variation with JMP
Discrete Distributions as Models of Real Processes
Application
Overview
Continuous Data and Probability
Density Functions
The Normal Model
Normal Calculations
Checking Data for the Suitability of a Normal Model
Generating Pseudo-Random Normal Data
Application
Chapter 8: Sampling and Sampling Distributions
Overview
Why Sample?
Methods of Sampling
Using JMP to Select a Simple Random Sample
Variability Across Samples: Sampling Distributions
Application
Chapter 9: Review of Probability and Probabilistic Sampling
Overview
Probability Distributions and Density Functions
The Normal and t Distributions
The Usefulness of Theoretical Models
When Samples Surprise Us: Ordinary and Extraordinary Sampling Variability
Conclusion
Chapter 10: Inference for a Single Categorical Variable
Overview
Two Inferential Tasks
Statistical Inference Is Always Conditional
Using JMP to Conduct a Significance Test
Confidence Intervals
Using JMP to Estimate a Population Proportion
A Few Words about Error
Application
Chapter 11: Inference for a Single Continuous Variable
Overview
Conditions for Inference
Using JMP to Conduct a Significance Test
What If Conditions Are Not Satisfied?
Using JMP to Estimate a Population Mean
Matched Pairs: One Variable, Two Measurements
Application
Overview
Chi-Square Goodness-of-Fit Test
Inference for Two Categorical Variables
Contingency Tables Revisited
Chi-Square Test of Independence
Application
Chapter 13: Two-Sample Inference for a Continuous Variable
Overview
Conditions for Inference
Using JMP to Compare Two Means
Using JMP to Compare Two Variances
Application
Chapter 14: Analysis of Variance
Overview
What Are We Assuming?
One-Way ANOVA
What If Conditions Are Not Satisfied?
Including a Second Factor with Two-Way ANOVA
Application