Statistical Tableau

Table of contents

1. Preface
   1. This Book’s Purpose
   2. This Book’s Audience
   3. This Book’s Structure
   4. Conventions Used in This Book
   5. O’Reilly Online Learning
   6. How to Contact Us
   7. Acknowledgments
2. 1. Introduction
   1. Introduction to Tableau
      1. Common Terms of the Authoring Interface of Tableau Desktop
      2. Example of the Step-by-Step Instructions Throughout This Book
   2. Introduction to Statistics
      1. Common Statistical Terms
      2. Practical Application Through a Case Study
   3. Data Visualization and Statistics
   4. Summary
3. 2. Overview of the Analytics Pane
   1. What Is the Analytics Pane?
   2. Implementing Summarization Options from the Analytics Pane
   3. Implementing Model Options from the Analytics Pane
   4. Implementing Custom Options from the Analytics Pane
   5. Summary
4. 3. Benchmarking in Tableau
   1. What Is a Benchmark?
      1. Internal Benchmarking
      2. External Benchmarking
   2. Implementing Benchmarks in Tableau
      1. Static Reference Line
      2. Dynamic Reference Line Using User-Driven Parameter
      3. Dynamic Reference Line Using Level-of-Detail Calculation
      4. Median with Quartiles
   3. Summary
5. 4. Understanding Normal Distribution Using Histograms
   1. Types of Distribution
      1. Uniform Distribution
      2. Bernoulli Distribution
      3. Exponential Distribution
      4. Normal Distribution
   2. Normal Distribution and Skewness
      1. Understanding Skewness
      2. Accounting for Skewness
   3. How to Visualize Distributions in Tableau Using Histograms
      1. Parametric Models
      2. Nonparametric Models
   4. Summary
6. 5. Understanding Confidence Intervals
   1. What Is a Confidence Interval?
   2. How to Calculate Confidence Intervals
   3. Interpreting the Results
   4. How to Calculate Confidence Intervals in Tableau
      1. Check the Confidence Interval You Solved by Hand
      2. Implement Confidence Intervals on a Sample Dataset
   5. Summary
7. 6. Anomaly Detection on Normally Distributed Data
   1. Understanding Standard Deviations
   2. How to Implement Standard Deviations in Tableau to Find Anomalies
   3. Understanding Median with Quartiles
   4. How to Use Median with Quartiles in Tableau to Find Anomalies
   5. Understanding Z-Score Tests
      1. How to Use Z-Scores in Tableau to Find Anomalies
   6. Summary
8. 7. Anomaly Detection on Nonnormalized Data
   1. Understanding Median Absolute Deviation
   2. How to Implement Median Absolute Deviations in Tableau
   3. Understanding Modified Z-Score
   4. How to Implement Modified Z-Scores in Tableau
   5. Understanding Tukey’s Fences
      1. How to Implement Tukey’s Fences in Tableau
   6. Summary
9. 8. Linear Regression in Tableau
   1. Linear Regression Model
      1. Linear Regression Expressed Mathematically
      2. Simple Linear Regression Example
      3. Assumptions of Linear Regression Models
   2. Implementing Linear Regression in Tableau
      1. R-squared
      2. P-value
      3. Interpreting the Detailed Summary Statistics
   3. Summary
10. 9. Polynomial Regression in Tableau
    1. What Is Polynomial Regression?
    2. Polynomial Regression Equation
       1. Polynomial Regression Expressed Mathematically
       2. Choosing the Right Model
    3. How to Implement Polynomial Regression in Tableau
    4. Summary
11. 10. Forecasting in Tableau
    1. What Is Exponential Smoothing?
    2. Exponential Smoothing Equations
    3. How to Implement Forecast Models in Tableau
       1. Forecast Options
       2. Describe Forecast
    4. Summary
12. 11. Clustering in Tableau
    1. What Is K-Means Clustering?
       1. K-Means Conceptual Example
       2. K-Means Example with Real Values
    2. Supervised Versus Unsupervised Learning Methods
       1. Supervised Learning
       2. Unsupervised Learning
    3. How to Implement Clustering in Tableau
    4. Summary
13. 12. Creating an External Connection to R Using Tableau
    1. What Is R Code?
       1. Key Features
       2. What Is RStudio?
    2. Installing R and RStudio
       1. Installing R
       2. Installing RStudio
    3. Establishing an External Connection in Tableau
    4. Summary
14. 13. Creating an External Connection to Python Using Tableau
    1. What Is Python?
       1. Key Features
       2. What Is Anaconda?
    2. Installing Python and Anaconda
    3. Establishing an External Connection to Python in Tableau
    4. Summary
15. 14. Understanding Multiple Linear Regression in R and Python
    1. What Is Multiple Linear Regression?
    2. Multiple Linear Regression Equation
    3. How to Implement Multiple Linear Regression in R
    4. How to Implement Multiple Linear Regression in Python
    5. Summary
16. 15. Using External Connections in Tableau
    1. Script Functions in Tableau
       1. Passing Arguments in a Tableau Script Function
       2. Table Calculations and Knowing the Level of Detail
    2. Example of Using an External Connection to R from Tableau
    3. Example of Using an External Connection to Python from Tableau
    4. Summary
17. Index
18. About the Author