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

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

In this chapter, we are going to apply our knowledge of the statistical tests of relationship confidence to build a predictive model.

Because we are now working with a multivariable regression model, we have to explore the most influential variables to build the best prediction case.

We will work with a case with several values, and we will use our judgment and statistical tests to ascertain which two variables have more influence over the prediction that we are looking for.

We have to apply our judgment because it could be the case that the f-statistics and p-value accept the null hypothesis that the slope is equal to zero for a variable. However, the relationship is validated by the coefficients of determination and correlation, as well as by the f-statistics. f-statistics is a test to reject the hypothesis that the slope is equal to zero, meaning that there is no relationship between the regression...

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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

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

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

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

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