You're reading from Data Forecasting and Segmentation Using Microsoft Excel Perform data grouping, linear predictions, and time series machine learning statistics without using code

Product type Paperback

Published in May 2022

Publisher Packt

ISBN-13 9781803247731

Length 324 pages

Edition 1st Edition

Languages

C++

Tools

Excel

Concepts

Data Analysis

Author (1):

Fernando Roque

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Table of Contents (19) Chapters

Preface

1. Part 1 – An Introduction to Machine Learning Functions

2. Chapter 1: Understanding Data Segmentation FREE CHAPTER

3. Chapter 2: Applying Linear Regression

4. Chapter 3: What is Time Series?

5. Part 2 – Grouping Data to Find Segments and Outliers

6. Chapter 4: Introduction to Data Grouping

7. Chapter 5: Finding the Optimal Number of Single Variable Groups

8. Chapter 6: Finding the Optimal Number of Multi-Variable Groups

9. Chapter 7: Analyzing Outliers for Data Anomalies

10. Part 3 – Simple and Multiple Linear Regression Analysis

11. Chapter 8: Finding the Relationship between Variables

12. Chapter 9: Building, Training, and Validating a Linear Model

13. Chapter 10: Building, Training, and Validating a Multiple Regression Model

14. Part 4 – Predicting Values with Time Series

15. Chapter 11: Testing Data for Time Series Compliance

16. Chapter 12: Working with Time Series Using the Centered Moving Average and a Trending Component

17. Chapter 13: Training, Validating, and Running the Model

18. Other Books You May Enjoy

Calculating the r-squared

The r-squared is the coefficient of determination that was calculated earlier. It tells us the factor of separation between the Y value (miles per gallon) of the dataset (the blue dots) and Y' (miles per gallon calculated by the model – the gray line) from the average of Y (the red line) as an origin line. Consult the chart to understand this relationship.

This is the explained variation (SSR) divided by the total variation (SST):

Figure 9.26 – SST, SSR, and SSE

The coefficient of determination

The coefficient of determination is one of the indicators of the relationship strength between the variables:

r2 = Explained Variation Regression Sum of Squares SSR divided by Total Variation Sum of Squares SST

For our example, we calculated these variations:

Figure 9.27 – Calculations for SSE and SST – the sum of the SS errors is 227.18 and the sum for the SS total is 837...

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You're reading from Data Forecasting and Segmentation Using Microsoft Excel Perform data grouping, linear predictions, and time series machine learning statistics without using code

Table of Contents (19) Chapters

Calculating the r-squared

The coefficient of determination

Authors (1)

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You're reading from Data Forecasting and Segmentation Using Microsoft Excel Perform data grouping, linear predictions, and time series machine learning statistics without using code

Table of Contents (19) Chapters

Calculating the r-squared

The coefficient of determination

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Authors (1)

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