You are previewing Statistical Analysis for Business Using JMP(R): A Student's Guide.
O'Reilly logo
Statistical Analysis for Business Using JMP(R): A Student's Guide

Book Description

A complete and thorough introduction to business statistics using JMP. While the book is designed for introductory business statistics courses at the undergraduate or MBA level, industry professionals wanting to brush up on their knowledge of statistics and those wanting an introduction to using JMP for statistical analysis will also find it useful.

Table of Contents

  1. Cover Page
  2. Copyright
  3. Contents
  4. Preface
  5. Acknowledgments
  6. Part 1 Basic Foundation
    1. Chapter 1 Introduction to Statistics
      1. Why Study Statistics?
      2. The Traditional View of Statistics
      3. The Modern View of Statistics
        1. A Process View of Organizations
        2. Changes in Statistical Pedagogy
        3. Changes in Information Technology
        4. How Is This Modern View of Statistics Different?
      4. Important Concepts in Statistics
        1. Populations and Samples
        2. Parameters and Statistics
        3. Descriptive and Inferential Statistics
        4. Sampling and Nonsampling Error
        5. Statistical Inference and the Discovery Process
      5. Collecting Data
        1. Collecting Primary Data
        2. Surveys and Observation
        3. Experiments and Post-Hoc Studies
        4. A Classification of Data-Gathering Situations
      6. Types of Data
        1. Quantitative versus Qualitative Variables4
        2. Discrete and Continuous Variables
        3. Scales of Measurement
      7. Computers and Statistical Analysis: Introducing JMP
      8. The Inland Northwest Credit Union
      9. Summary
      10. Chapter Glossary
      11. Questions and Problems
      12. References
      13. Notes
    2. Chapter 2 Introduction to JMP
      1. JMP Software
        1. The JMP Starter
      2. The Situation at INCU
      3. Creating Data Tables
        1. Adding Columns
        2. Entering Data into the Data Table
        3. Data Types and Modeling Types
      4. Working with Data Tables
        1. Combining Data Tables
        2. Using Value Labels
      5. Reshaping Data Tables
        1. Sorting Data Tables
        2. Filtering Data and Creating Subsets of Data Tables
      6. Analysis Platforms
        1. The Distribution Platform
        2. Fit Y by X Platform
        3. Matched Pairs Platform
        4. Fit Model Platform
      7. Working with Reports
        1. Formatting Report Tables
        2. Copying and Printing Reports
        3. Performing Further Analysis
      8. Summary
      9. Chapter Glossary
      10. Questions and Problems
      11. Notes
  7. Part 2 Visualizing Data: Descriptive Statistics
    1. Chapter 3 Visualizing Data in Tables and Graphs
      1. The Situation at INCU
      2. Statistical Tables
        1. Summary Tables
        2. Tabulate Command
      3. The Graph Command
      4. Charts for Qualitative Data
        1. Bar Charts
        2. Pie Charts
        3. Tree Maps
      5. Graphs for Quantitative Data
        1. Histograms
        2. Stem-and-Leaf Diagrams
        3. Line Charts
      6. Looking at Relationships
        1. Scatter Plots
        2. Bubble Plots
        3. Contingency Tables
        4. Mosaic Plots
      7. Exploring Data Using Graph Builder
      8. Summary
      9. Chapter Glossary
      10. Questions and Problems
      11. References
      12. Notes
    2. Chapter 4 Summarizing Univariate Data: The Distribution Platform
      1. The Situation at INCU
      2. The Distribution Platform
      3. Summarizing Quantitative Variables
        1. Graphic Analysis Panel
        2. Quantiles Panel
        3. Moments Panel
        4. Additional Moments
      4. Summary Measures for Qualitative Variables
        1. Frequencies Panel
      5. Summarizing by a Qualitative Variable
      6. Summary
      7. Chapter Glossary
      8. Questions and Problems
      9. Notes
  8. Part 3 Basic Foundation
    1. Chapter 5 Foundations of Statistical Inference
      1. The Situation at INCU
      2. Populations and Samples
        1. Population Parameters and Sample Statistics
      3. Sampling in Statistics
        1. Simple Random Samples
        2. Sampling and Inferential Statistics
      4. The Meaning of Probability
      5. Probability Distributions
        1. Discrete Probability Distributions
        2. Continuous Probability Distributions
      6. The Concept of a Sampling Distribution
        1. Sampling Distributions as a Population of Values
        2. Sampling Distributions as a Probability Distribution
      7. Sampling Distributions for Common Sample Statistics
        1. Sampling Distributions for the Mean
        2. Sampling Distributions for the Standard Deviation and Variance
        3. Sampling Distributions for the Proportion
        4. Sampling Distributions for the Median
        5. The Concept of Bootstrapping
      8. Summary
      9. Chapter Glossary
      10. Questions and Problems
      11. References
      12. Notes
    2. Chapter 6 Introduction to Statistical Inference
      1. The Situation at INCU
      2. Introduction to Estimation
        1. The Concept of Sampling Error
        2. Interval Estimation
        3. Finding the Right Sample Size
      3. Introduction to Hypothesis Testing
        1. p-Values
        2. Tests of Equivalence
      4. JMP and Inferences about One Variable
      5. Inferences about Means
      6. Inferences about Variances and Standard Deviations
      7. Inferences about Medians
        1. Sign Test for Medians
        2. Bootstrapping Inference about the Median
      8. Inferences about Proportions
        1. Finding the Right Sample Size for Proportions
      9. Summary
      10. Chapter Glossary
      11. Questions and Problems
      12. References
      13. Notes
  9. Part 4 The Effects of One Variable on Another
    1. Chapter 7 Effects of a Qualitative Variable on a Quantitative Variable
      1. The Situation at INCU
      2. Qualitative Variables and Grouping
        1. Independent and Dependent Variables (Factor and Response)
      3. Independent versus Dependent Groups
      4. Qualitative Variables with Two Levels
        1. Independent Groups
        2. Dependent Groups
      5. Qualitative Variables with Three or More Levels
        1. Tests for Three or More Means
        2. Tests for Three of More Variances
        3. Tests for Three or More Medians
      6. Summary
      7. Chapter Glossary
      8. Questions and Problems
      9. References
      10. Notes
    2. Chapter 8 Effects of a Qualitative Variable on a Qualitative Variable
      1. The Situation at INCU
      2. The Fit Y by X Platform for Qualitative Variables
      3. The Logic of Chi-Square Tests for Contingency Tables
      4. Correspondence Analysis
      5. Two by Two Contingency Tables
        1. Contingency Tables and the Classic Z Test
        2. Risk Difference
      6. Summary
      7. Chapter Glossary
      8. Questions and Problems
      9. References
      10. Notes
    3. Chapter 9 Effects of a Quantitative Variable on a Quantitative Variable
      1. The Situation at INCU
      2. Correlation Analysis
        1. The Bivariate Platform and the Density Ellipse
        2. Correlation Coefficient
      3. Regression Analysis
        1. Assumptions of Linear Regression
        2. Regression Analysis in the Bivariate Platform
      4. Summary
      5. Chapter Glossary
      6. Questions and Problems
      7. Notes
    4. Chapter 10 Effects of a Quantitative Variable on a Qualitative Variable
      1. The Situation at INCU
      2. Binomial Regression and the Logic of Logistic Regression
      3. The Logistic Platform
        1. Logistic Regression
        2. Inverse Prediction
      4. Multinomial Regression
        1. A Multinomial Example
        2. Multinomial Logistic Regression and ANOVA
      5. Summary
      6. Chapter Glossary
      7. Questions and Problems
      8. Notes
  10. Part 5 Relationships between Multiple Variables
    1. Chapter 11 Introduction to Multivariate Statistics: Multiple Regression
      1. The Situation at INCU
      2. Introduction to Multivariate Analysis: The JMP Platforms
      3. Correlation Analysis and the Multivariate Platform
        1. Multivariate Options
      4. Multiple Regression and the Fit Model Platform
        1. The Fit Model Platform
        2. Multiple Regression Results
      5. Regression Diagnostics
        1. Analysis of Residuals
        2. Influence: Leverage and Outliers
        3. Multicollinearity in Regression
      6. Selecting Factors for Inclusion in the Model
        1. Stepwise Regression
      7. Nominal Variables in Regression
        1. Dummy Coding
      8. Summary
      9. Chapter Glossary
      10. Questions and Problems
      11. References
      12. Notes
  11. Index