Python engine (reticulate) for R Markdown for interoperability between Python and R chunks.

Predicting Energy Efficiency Using Multiple Linear Regression

Model Development to Predict Used Home Prices Using Multiple Regression

Hypothesis Testing using Bootstrap, Resampling, and Confidence Intervals

A Practical Application of Hypothesis Testing

Using Sampling Distributions for High-Dimensional Data

An Algorithmic EDA of the Complete Data Set - Titanic.csv

Feature Engineering on the Training and Test Sets - Titanic.csv

Split, Transform and Scale the Data Set - Titanic.csv

Non-graphical Univariate and Bivariate Statistical Analysis

From Univariate to Bivariate and Multivariate Analysis

Univariate Visualization and Analysis on the Data Set (titanic.csv)

Assess, Filter, Clean, Present the Data Set (titanic.csv)

Examine a dataset