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

Exploring the variables with more influence

In this section, we will undertake a multi-regression exercise exploring the variables that could influence the sales revenue of a business. Please download the Excel worksheet from the Technical requirements section at the beginning of this chapter. Open the Sales inventory sheet. The first task of the job is to find which are the two most influential variables, X and Y, over a sales-revenue results variable. The variables on the worksheet that could influence sales and revenue are as follows:

Number of hours out of service
Material rotation
Online marketing
Sector sales
Distance (Km) to competing stores

To find the two most influential variables, follow this process:

Use the t-statistics and the p-value analysis returned by the regression function. To validate the variables, examine the 3D chart and ascertain whether there is an obvious relationship between them.
Understand the influence of...

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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

Exploring the variables with more influence

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Table of Contents (19) Chapters

Exploring the variables with more influence

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