Updated for JMP 10, the book provides hands-on tutorials with just the right amount of conceptual and motivational material to illustrate how to use the intuitive interface for data analysis in JMP. Features concept-specific tutorials, examples, brief reviews of concepts, step-by-step illustrations, and exercises.
Table of Contents
JMP Right In
- First Session
- Customize JMP
- Modeling Type
- The Personality of JMP
Data Tables, Reports, and Scripts
- The Ins and Outs of a JMP Data Table
- Creating a New JMP Table
- Importing Data
- Moving Data Out of JMP
- Working with Graphs and Reports
- Juggling Data Tables
- Creating Summary Statistics
- Working with Scripts
Formula Editor Adventures
- The Formula Editor Window
- Formula Editor: Pieces and Parts
- Function Definitions
- Some Nice Examples Involving Dates
- Tips on Building Formulas
- What Are Statistics?
Univariate Distributions: One Variable, One Sample
- Looking at Distributions
- Describing Distributions of Values
- Statistical Inference on the Mean
- Practical Significance vs. Statistical Significance
- Examining for Normality
- Special Topic: Practical Difference
- Special Topic: Simulating the Central Limit Theorem
- Seeing Kernel Density Estimates
The Difference Between Two Means
Two Independent Groups
- When the Difference Isn’t Significant
- Check the Data
- Launch the Fit Y by X Platform
- Examine the Plot
- Display and Compare the Means
- Inside the Student’s t-Test
- Equal or Unequal Variances?
- One-Sided Version of the Test
- Analysis of Variance and the All-Purpose F-Test
- How Sensitive Is the Test? How Many More Observations Are Needed?
- When the Difference Is Significant
- Normality and Normal Quantile Plots
- Testing Means for Matched Pairs
- Two Extremes of Neglecting the Pairing Situation: A Dramatization
- A Nonparametric Approach
Comparing Many Means: One-Way Analysis of Variance
- What Is a One-Way Layout?
- Comparing and Testing Means
- Adjusting for Multiple Comparisons
- Are the Variances Equal Across the Groups?
- Testing Means with Unequal Variances
- Nonparametric Methods
Fitting Curves through Points: Regression
- Polynomial Models
- Transformed Fits
- Are Graphics Important?
- Why It’s Called Regression
- What Happens When X and Y Are Switched?
- Categorical Situations
- Categorical Responses and Count Data: Two Outlooks
- A Simulated Categorical Response
- The X2 Pearson Chi-Square Test Statistic
- The G2 Likelihood-Ratio Chi-Square Test Statistic
- Univariate Categorical Chi-Square Tests
- Fitting Categorical Responses to Categorical Factors: Contingency Tables
- Two-Way Tables: Entering Count Data
- If You Have a Perfect Fit
- Special Topic: Correspondence Analysis— Looking at Data with Many Levels
- Continuous Factors with Categorical Responses: Logistic Regression
- Surprise: Simpson's Paradox: Aggregate Data versus Grouped Data
- Generalized Linear Models
- Parts of a Regression Model
- Regression Definitions
- A Multiple Regression Example
- Mining Data with Stepwise Regression
Fitting Linear Models
The General Linear Model
- Kinds of Effects in Linear Models
- Coding Scheme to Fit a One-Way anova as a Linear Model
- Regressor Construction
- Interpretation of Parameters
- Predictions Are the Means
- Parameters and Means
- Analysis of Covariance: Continuous and Categorical Terms in the Same Model
- The Prediction Equation
- The Whole-Model Test and Leverage Plot
- Effect Tests and Leverage Plots
- Least Squares Means
- Lack of Fit
- Separate Slopes: When the Covariate Interacts with a Categorical Effect
- Two-Way Analysis of Variance and Interactions
- Optional Topic: Random Effects and Nested Effects
Design of Experiments
- A Simple Design
- Using the Custom Designer
- An Interaction Model: The Reactor Data
- Some Routine Screening Examples
- Response Surface Designs
- Split Plot Designs
- Design Strategies
- Design of Experiments Glossary
Bivariate and Multivariate Relationships
- Bivariate Distributions
- Density Estimation
- Correlations and the Bivariate Normal
- Outliers in Three and More Dimensions
- Identify Variation with Principal Components Analysis
- Discriminant Analysis
- Cluster Analysis
- Some Final Thoughts
- Exploratory Modeling
Control Charts and Capability
- What Does a Control Chart Look Like
- Types of Control Charts
- Control Chart Basics
- Control Charts for Variables Data
- Variables Charts using Control Chart Builder
- Control Charts for Attributes Data
- Specialty Charts
- Capability Analysis
- A Few Words About Measurement Systems
Mechanics of Statistics
- Springs for Continuous Responses
- Mechanics of Fit for Categorical Responses
- Analyze and Graph Menu Commands
Answers to Selected Exercises
- Chapter 4, "Formula Editor Adventures"
- Chapter 7, "Univariate Distributions: One Variable, One Sample"
- Chapter 8, "The Difference Between Two Means"
- Chapter 9, "Comparing Many Means: One-Way Analysis of Variance"
- Chapter 10, "Fitting Curves through Points: Regression"
- Chapter 11, "Categorical Distributions"
- Chapter 12, "Categorical Models"
- Chapter 13, "Multiple Regression"
- Chapter 14, "Fitting Linear Models"
- Chapter 15, "Design of Experiments"
- Chapter 16, "Bivariate and Multivariate Relationships"
- Chapter 17, "Exploratory Modeling"
- Chapter 18, "Control Charts and Capability"
- References and Data Sources
- Technology License Notices
- Title: JMP Start Statistics, 5th Edition
- Release date: March 2012
- Publisher(s): SAS Institute
- ISBN: 9781612903071