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Data Forecasting and Segmentation Using Microsoft Excel

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

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Product type Paperback
Published in May 2022
Publisher Packt
ISBN-13 9781803247731
Length 324 pages
Edition 1st Edition
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Author (1):
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Fernando Roque Fernando Roque
Author Profile Icon Fernando Roque
Fernando Roque
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Table of Contents (19) Chapters Close

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

Understanding outliers

Many data points are far away from the group centroid or average, affecting the value of the standard value. Remember that the optimal case is to have a compact group with a small standard value. These data points are outliers that don't comply with the characteristics of the group or the general data. These outliers deserve further investigation because they could have suspicious behavior (for example, fraud or peaks in demand) that could affect the performance of the system, such as network traffic. Look at Figure 4.14 to examine the outliers of the groups of one variable and the outliers of the 3D chart:

Figure 4.14 – Outliers for one variable and three variables

Group Number 3 is the outlier of the one-variable classification. Notice that the points have a large separation from the centroid. The standard deviation has a large amplitude. This group has different behavior compared with the other two, which are compact...

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