Box-Cox transformation in Julia

Statistical analysis of the Los Angeles real estate market in form of assessed values and rental prices

Learn about Simple Linear Regression for Data Science

Projects for a biological data analysis course taught by Dr. Diane Thomson at the Keck Science Institute during Fall 2021.

Applied Statistics I, 2021, UNC at Chapel Hill-linear regression

This project analyzes and preprocesses the Online Retail dataset to uncover insights into customer purchasing behaviors, sales trends, and product performance. It includes data cleaning, exploration, and visualization, with the goal of enhancing understanding of online retail dynamics.

Analysis of Skewness and Kurtosis in Stock Return data and their Transformations

The R package ClusROC

socio-economic segmentation analysis to identify global development patterns. We analyze key indicators: child mortality, income, and GDP per capita. Our analysis employs data cleaning, exploratory analysis, Box-Cox transformation for normalization, and KMeans clustering to segment countries into developmental categories

A Python-based utility for testing and visualizing data transformations. Includes normality tests (Shapiro-Wilk and Lilliefors), a variety of transformation methods, and visual analysis tools for histogram and Q-Q plots.

This repository contains assignments #3 that was completed as a part of "FIT5196 Data Wrangling", taught at Monash Uni in S2 2020.

A Python-based utility for testing and visualizing data transformations. Includes normality tests (Shapiro-Wilk and Lilliefors), a variety of transformation methods, and visual analysis tools for histogram and Q-Q plots.