Understanding part (semi partial) and partial correlation coefficients in multiple regression model. Deriving the multiple R-Squared and beta coefficients from basics. Inspired from Business Analytics: The Science of Data-Driven Decision Making by Dinesh Kumar.
Recommendation systems using associate mining rules
Discussion on hypothesis testing. Introduction to z-test and t-test, Code for visualization of z-test and t-test.
Links to all other posts in a structured way. Table of contents.
Explains why basics are important using a simple example.
Tutorial on Multicollinearity which is the third part of EDA. Plot of Correlation matrix and network for in-time problem with reusable code.
Tutorial on Multivariate analysis which is the second part of EDA. Explained using in-time problem with reusable R code.
Getting traffic, vehicle used, location and journey time from Google Maps. Integrating these factors for in-time problem.
Explanation of class size paradox using Amrita University placement data. Contains reusable R code for web scraping.
Tutorial on Univariate analysis which is the first part of EDA. Explained using in-time problem with reusable R code.