R for Programming

A repository for Data Mining, Forecasting & Linear Regression.

Thanks for stopping by!

This repository is part of projects and statistical methodologies I've learned at Baruch College and other online courses. The goal of this is to explore basic statistics analysis using R. When it comes to statistical concepts, it's important to know when to apply these concepts when analyzing data. Topics such as linear regression, correlation, clustering, IQR, null vs. alternative hypothesis will be introduced in this repo.

Courses:

• CIS/STA 3920 - Data Mining for Business Analytics
• STA 3155 - Regression and Forecasting Models for Business Applications

Books:

• Business Statistics (4nd edition), by Sharpe, De Veaux, and Velleman
• Introduction to Data Mining (1st Edition) by Pang-Ning Tan, Michael Steinbach and Vipin Kumar
• An Introduction to Statistical Learning: with Applications in R by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani.

Helpful links:

• Colors in R!
• Graphical Parameters
• What are QQ plots?
• Ladder of Powers
• Identifying Outliers