Book Image

Data Forecasting and Segmentation Using Microsoft Excel

By : Fernando Roque
Book Image

Data Forecasting and Segmentation Using Microsoft Excel

By: Fernando Roque

Overview of this book

Data Forecasting and Segmentation Using Microsoft Excel guides you through basic statistics to test whether your data can be used to perform regression predictions and time series forecasts. The exercises covered in this book use real-life data from Kaggle, such as demand for seasonal air tickets and credit card fraud detection. You’ll learn how to apply the grouping K-means algorithm, which helps you find segments of your data that are impossible to see with other analyses, such as business intelligence (BI) and pivot analysis. By analyzing groups returned by K-means, you’ll be able to detect outliers that could indicate possible fraud or a bad function in network packets. By the end of this Microsoft Excel book, you’ll be able to use the classification algorithm to group data with different variables. You’ll also be able to train linear and time series models to perform predictions and forecasts based on past data.
Table of Contents (19 chapters)
1
Part 1 – An Introduction to Machine Learning Functions
5
Part 2 – Grouping Data to Find Segments and Outliers
10
Part 3 – Simple and Multiple Linear Regression Analysis
14
Part 4 – Predicting Values with Time Series

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...