Statistical Tableau - Helion
ebook
Autor: Ethan LangISBN: 9781098151751
stron: 316, Format: ebook
Data wydania: 2024-05-02
Księgarnia: Helion
Cena książki: 150,87 zł (poprzednio: 206,67 zł)
Oszczędzasz: 27% (-55,80 zł)
In today's data-driven world, understanding statistical models is crucial for effective analysis and decision making. Whether you're a beginner or an experienced user, this book equips you with the foundational knowledge to grasp and implement statistical models within Tableau. Gain the confidence to speak fluently about the models you employ, driving adoption of your insights and analysis across your organization.
As AI continues to revolutionize industries, possessing the skills to leverage statistical models is no longer optional—it's a necessity. Stay ahead of the curve and harness the full potential of your data by mastering the ability to interpret and utilize the insights generated by these models.
Whether you're a data enthusiast, analyst, or business professional, this book empowers you to navigate the ever-evolving landscape of data analytics with confidence and proficiency. Start your journey toward data mastery today.
In this book, you will learn:
- The basics of foundational statistical modeling with Tableau
- How to prove your analysis is statistically significant
- How to calculate and interpret confidence intervals
- Best practices for incorporating statistics into data visualizations
- How to connect external analytics resources from Tableau using R and Python
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Spis treści
Statistical Tableau eBook -- spis treści
- Preface
- This Books Purpose
- This Books Audience
- This Books Structure
- Conventions Used in This Book
- OReilly Online Learning
- How to Contact Us
- Acknowledgments
- 1. Introduction
- Introduction to Tableau
- Common Terms of the Authoring Interface of Tableau Desktop
- Example of the Step-by-Step Instructions Throughout This Book
- Introduction to Statistics
- Common Statistical Terms
- Practical Application Through a Case Study
- Setting up the hypothesis test
- Chi-square test
- Conclusions drawn from statistical analysis
- Data Visualization and Statistics
- Summary
- Introduction to Tableau
- 2. Overview of the Analytics Pane
- What Is the Analytics Pane?
- Implementing Summarization Options from the Analytics Pane
- Implementing Model Options from the Analytics Pane
- Implementing Custom Options from the Analytics Pane
- Summary
- 3. Benchmarking in Tableau
- What Is a Benchmark?
- Internal Benchmarking
- External Benchmarking
- Implementing Benchmarks in Tableau
- Static Reference Line
- Dynamic Reference Line Using User-Driven Parameter
- Dynamic Reference Line Using Level-of-Detail Calculation
- Median with Quartiles
- Summary
- What Is a Benchmark?
- 4. Understanding Normal Distribution Using Histograms
- Types of Distribution
- Uniform Distribution
- Bernoulli Distribution
- Exponential Distribution
- Normal Distribution
- Normal Distribution and Skewness
- Understanding Skewness
- Accounting for Skewness
- How to Visualize Distributions in Tableau Using Histograms
- Parametric Models
- Nonparametric Models
- Summary
- Types of Distribution
- 5. Understanding Confidence Intervals
- What Is a Confidence Interval?
- How to Calculate Confidence Intervals
- Interpreting the Results
- How to Calculate Confidence Intervals in Tableau
- Check the Confidence Interval You Solved by Hand
- Implement Confidence Intervals on a Sample Dataset
- Summary
- 6. Anomaly Detection on Normally Distributed Data
- Understanding Standard Deviations
- How to Implement Standard Deviations in Tableau to Find Anomalies
- Understanding Median with Quartiles
- How to Use Median with Quartiles in Tableau to Find Anomalies
- Understanding Z-Score Tests
- How to Use Z-Scores in Tableau to Find Anomalies
- Summary
- 7. Anomaly Detection on Nonnormalized Data
- Understanding Median Absolute Deviation
- How to Implement Median Absolute Deviations in Tableau
- Understanding Modified Z-Score
- How to Implement Modified Z-Scores in Tableau
- Understanding Tukeys Fences
- How to Implement Tukeys Fences in Tableau
- Summary
- 8. Linear Regression in Tableau
- Linear Regression Model
- Linear Regression Expressed Mathematically
- Simple Linear Regression Example
- Assumptions of Linear Regression Models
- Implementing Linear Regression in Tableau
- R-squared
- P-value
- Interpreting the Detailed Summary Statistics
- Summary
- Linear Regression Model
- 9. Polynomial Regression in Tableau
- What Is Polynomial Regression?
- Polynomial Regression Equation
- Polynomial Regression Expressed Mathematically
- Choosing the Right Model
- How to Implement Polynomial Regression in Tableau
- Summary
- 10. Forecasting in Tableau
- What Is Exponential Smoothing?
- Exponential Smoothing Equations
- How to Implement Forecast Models in Tableau
- Forecast Options
- Forecast Length
- Source Data
- Forecast Model
- Describe Forecast
- Forecast Options
- Summary
- 11. Clustering in Tableau
- What Is K-Means Clustering?
- K-Means Conceptual Example
- K-Means Example with Real Values
- Supervised Versus Unsupervised Learning Methods
- Supervised Learning
- Unsupervised Learning
- How to Implement Clustering in Tableau
- Summary
- What Is K-Means Clustering?
- 12. Creating an External Connection to R Using Tableau
- What Is R Code?
- Key Features
- What Is RStudio?
- Installing R and RStudio
- Installing R
- Installing RStudio
- Establishing an External Connection in Tableau
- Summary
- What Is R Code?
- 13. Creating an External Connection to Python Using Tableau
- What Is Python?
- Key Features
- What Is Anaconda?
- Installing Python and Anaconda
- Establishing an External Connection to Python in Tableau
- Summary
- What Is Python?
- 14. Understanding Multiple Linear Regression in R and Python
- What Is Multiple Linear Regression?
- Multiple Linear Regression Equation
- How to Implement Multiple Linear Regression in R
- How to Implement Multiple Linear Regression in Python
- Summary
- 15. Using External Connections in Tableau
- Script Functions in Tableau
- Passing Arguments in a Tableau Script Function
- Table Calculations and Knowing the Level of Detail
- Example of Using an External Connection to R from Tableau
- Example of Using an External Connection to Python from Tableau
- Summary
- Script Functions in Tableau
- Index