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Analyzing and Interpreting Continuous Data Using JMP®: A Step-by-Step Guide

Book Description

Based on real-world applications, Analyzing and Interpreting Continuous Data Using JMP: A Step-by-Step Guide, by Jose Ramirez, Ph.D., and Brenda S. Ramirez, M.S., combines statistical instructions with a powerful and popular software platform to solve common problems in engineering and science. In the many case studies provided, the authors clearly set up the problem, explain how the data were collected, show the analysis using JMP, interpret the output in a user-friendly way, and then draw conclusions and make recommendations. This step-by-step format enables users new to statistics or JMP to learn as they go, but the book will also be helpful to those with some familiarity with statistics and JMP. The book includes a foreword written by Professor Douglas C. Montgomery.

Table of Contents

  1. Copyright
  2. Dedication
  3. Foreword
  4. Acknowledgments
  5. 1. Using This Book
    1. 1.1. Origins of This Book
    2. 1.2. Purpose
    3. 1.3. Audience
    4. 1.4. Prerequisites
    5. 1.5. What's Unique About This Book?
    6. 1.6. Chapter Contents
      1. Chapter 2 Overview of Statistical Concepts and Ideas
      2. Chapter 3 Characterizing the Measured Performance of a Material, Process, or Product
      3. Chapter 4 Comparing the Measured Performance of a Material, Process, or Product to a Standard
      4. Chapter 5 Comparing the Measured Performance of Two Materials, Processes, or Products
      5. Chapter 6 Comparing the Measured Performance of Several Materials, Processes, or Products
      6. Chapter 7 Characterizing Linear Relationships between Two Variables
    7. 1.7. Chapter Layout
    8. 1.8. Step-by-Step Analysis Instructions
    9. 1.9. JMP Software
      1. 1.9.1. JMP Help and Resources
        1. JMP Tutorials
        2. JMP Books
        3. JMP.com Resources
    10. 1.10. Scope
    11. 1.11. Typographical Conventions
      1. Statistics Typographical Conventions
      2. JMP Typographical Conventions
      3. JMP Figure Annotations
    12. 1.12. References
  6. 2. Overview of Statistical Concepts and Ideas
    1. Chapter Goals
    2. 2.1. Why Statistics?
    3. 2.2. Measurement Scales, Modeling Types, and Roles
      1. 2.2.1a. Nominal Scale
      2. 2.2.1b. Ordinal Scale
      3. 2.2.1c. Interval Scale
      4. 2.2.1d. Ratio Scale
      5. 2.2.2. Which Scale?
      6. 2.2.3. Responses and Factors
    4. 2.3. Statistical Inference: From a Sample to a Population
      1. 2.3.1. Random Sampling
      2. 2.3.2. Randomization
    5. 2.4. Descriptive Statistics and Graphical Displays
    6. 2.5. Quantifying Uncertainty: Common Probability Distributions
      1. 2.5.1. Normal Distribution
      2. Standard Normal Distribution μ = 0 and σ = 1
        1. Goodness of Fit
    7. 2.6. Useful Statistical Intervals
      1. 2.6.1. Confidence Interval for the Mean
      2. 2.6.2. Prediction Interval for One Future Observation
      3. 2.6.3. Tolerance Interval to Contain a Given Proportion p of the Sampled Population
      4. 2.6.4. What Does Confidence Level Mean?
    8. 2.7. Overview of Tests of Significance
      1. 2.7.1. Critical Components of a Test of Significance
      2. 2.7.2. A 7-Step Framework for Statistical Studies
    9. 2.8. Summary
    10. 2.9. References
  7. 3. Characterizing the Measured Performance of a Material, Process, or Product
    1. Chapter Goals
    2. 3.1. Problem Description
      1. What do we know about it?
      2. What is the question or uncertainty to be answered?
      3. How do we get started?
      4. What is an appropriate statistical technique to use?
    3. 3.2. Key Questions, Concepts, and Tools
    4. 3.3. Overview of Exploratory Data Analysis
      1. 3.3.1. Description and Some Applications
      2. 3.3.2. Descriptive Statistics
      3. 3.3.3. Graphs and Visualization Tools
        1. Histograms and Normal Quantile Plots
        2. Box Plots
        3. Process Behavior Charts and Homogeneity
      4. 3.3.4. Statistical Intervals
        1. Making Claims Using Statistical Intervals
    5. 3.4. Step-by-Step JMP Analysis Instructions
    6. 3.5. Summary
    7. 3.6. References
  8. 4. Comparing the Measured Performance of a Material, Process, or Product to a Standard
    1. Chapter Goals
    2. 4.1. Problem Description
      1. What do we know about it?
      2. What is the question or the uncertainty to be answered?
      3. How do we get started?
      4. What is an appropriate statistical technique to use?
    3. 4.2. Key Questions, Concepts, and Tools
    4. 4.3. Overview of One-Sample Tests of Significance
      1. 4.3.1. Description and Some Applications
      2. 4.3.2. Comparing Average Performance to a Standard
        1. The t-statistic
      3. 4.3.3. Comparing Performance Variation to a Standard
      4. 4.3.4. Sample Size Calculations for Comparing Performance to a Standard
    5. 4.4. Step-by-Step JMP Analysis Instructions
    6. 4.5. Testing Equivalence to a Standard
    7. 4.6. Summary
    8. 4.7. References
  9. 5. Comparing the Measured Performance of Two Materials, Processes, or Products
    1. Chapter Goals
    2. 5.1. Problem Description
      1. What do we know about it?
      2. What is the question or uncertainty to be answered?
      3. How do we get started?
      4. What is an appropriate statistical technique to use?
    3. 5.2. Key Questions, Concepts, and Tools
    4. 5.3. Overview of Two-Sample Significance Test
      1. 5.3.1. Description and Some Applications
      2. 5.3.2. Comparing Average Performance of Two Materials, Processes, or Products
        1. The Two-sample t-Statistic
      3. 5.3.3. What to Do When We Have Matched Pairs
      4. 5.3.4. Comparing the Performance Variation of Two Materials, Processes, or Products
      5. 5.3.5. Sample Size Calculations
    5. 5.4. Step-by-Step JMP Analysis Instructions
    6. 5.5. Testing Equivalence of Two Materials, Processes, or Products
    7. 5.6. Summary
    8. 5.7. References
  10. 6. Comparing the Measured Performance of Several Materials Processes, or Products
    1. Chapter Goals
    2. 6.1. Problem Description
      1. What do we know about it?
      2. What is the question or uncertainty to be answered?
      3. How do we get started?
      4. What is the appropriate statistical technique to use?
    3. 6.2. Key Questions, Concepts, and Tools
    4. 6.3. Overview of One-way ANOVA
      1. 6.3.1. Description and Some Applications
      2. 6.3.2. Comparing Average Performance of Several Materials, Processes, or Products
      3. 6.3.3. Multiple Comparisons to Detect Differences between Pairs of Averages
      4. 6.3.4. Comparing the Performance Variation of Several Materials, Processes, or Products
      5. 6.3.5. Sample Size Calculations
    5. 6.4. Step-by-Step JMP Analysis Instructions
    6. 6.5. Testing Equivalence of Three or More Populations
    7. 6.6. Summary
    8. 6.7. References
  11. 7. Characterizing Linear Relationships between Two Variables
    1. Chapter Goals
    2. 7.1. Problem Description
      1. What do we know about it?
      2. What is the question or uncertainty to be answered?
      3. How do we get started?
      4. What is an appropriate statistical technique to use?
    3. 7.2. Key Questions, Concepts, and Tools
    4. 7.3. Overview of Simple Linear Regression
      1. 7.3.1. Description and Some Applications
      2. 7.3.2. Simple Linear Regression Model
      3. 7.3.3. Partitioning Variation and Testing for Significance
      4. 7.3.4. Checking the Model Fit
      5. 7.3.5. Sampling Plans
    5. 7.4. Step-by-Step JMP Analysis Instructions
    6. 7.5. Einstein's Data: The Rest of the Story
    7. 7.6. Summary
    8. 7.7. References