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

Finding the groups and centroids of one-variable data with K-means and Excel

After we process the data, we can use pivot tables to research the group members and value ranges, the centroids and upper/lower values, and the possible outliers of the data.

With the pivot chart analysis, we will explore the following segment information:

Assigning values for every group
Calculating the centroid or the average point for every group
Exploring the range of values for each segment

This information will give us a complete picture of how the segment values range. With this information, we can plan a different strategy for each group. We will likely see that we have to create a subsegment of a group because it has a large standard deviation or many scattered points at a distance from its centroid. We will also identify the possible outliers for each group.

Assigning values for every group

We'll build a pivot table with the ID, OneVarGroups (data values), and...

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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

Finding the groups and centroids of one-variable data with K-means and Excel

Assigning values for every group

Authors (1)

Personalised recommendations for you

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

Finding the groups and centroids of one-variable data with K-means and Excel

Assigning values for every group

Unlock this book and the full library FREE for 7 days

Authors (1)

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