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

Statistical significance of the slope

Remember that the slope determines the relationship between the X and Y variables.

To check the significance of the slope of the variables' relationship and the viability to build a predictive model, we are going to use the t-test. The t-test requires two hypotheses:

H0 – null hypothesis: The slope equals zero. This means that there is no relationship between the variables.
HA – alternative hypothesis: The slope is NOT equal to zero. This means that the variables have a relationship.

The t-test calculation steps are as follows:

Calculate the s value by dividing the SSE by the number of data elements minus two. In this example, the number of elements of data is 159.
Divide the slope by the s value.
Check whether the t-test is greater than the critical value given by the t-test table (https://www.sjsu.edu/faculty/gerstman/StatPrimer/t-table.pdf). If the value is greater than the critical...

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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

Statistical significance of the slope

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Table of Contents (19) Chapters

Statistical significance of the slope

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