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Applied Supervised Learning with R

You're reading from  Applied Supervised Learning with R

Product type Book
Published in May 2019
Publisher
ISBN-13 9781838556334
Pages 502 pages
Edition 1st Edition
Languages
Authors (2):
Karthik Ramasubramanian Karthik Ramasubramanian
Profile icon Karthik Ramasubramanian
Jojo Moolayil Jojo Moolayil
Profile icon Jojo Moolayil
View More author details
Toc

Table of Contents (12) Chapters close

Applied Supervised Learning with R
Preface
1. R for Advanced Analytics 2. Exploratory Analysis of Data 3. Introduction to Supervised Learning 4. Regression 5. Classification 6. Feature Selection and Dimensionality Reduction 7. Model Improvements 8. Model Deployment 9. Capstone Project - Based on Research Papers Appendix

Categorical Dependent and Categorical Independent Variables


Moving on, let's take a look at the third hypothesis. To test the relationship between the categorical dependent variable and categorical independent variable, we can use the chi squared test.

For hypothesis 3, we define the following:

  • Null hypothesis: The campaign outcome has no relationship with clients who never married.

  • Alternate hypothesis: The campaign outcome has a relationship with clients who never married.

In the following exercise, we will leverage R's chi-square test function to validate the hypothesis..

Exercise 38: Hypothesis 3 Testing for Categorical Dependent Variables and Categorical Independent Variables

In this exercise, we will perform a statistical test using the chi-squared test. We use the chi-squared test because both the independent and dependent variables are categorical, particularly when testing the relationship between y and marital status.

Perform the following steps:

  1. Import the required libraries and create...

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