Learning mathematical methods of data analysis in the language R.

Library for processing and extracting assets for the 3D/ADV engine

Testing effects of missing data on phylogenetic inferences

A series of Jupyter notebooks, to know about Machine Learning, its implementation, and identifying its best practices.

All my R code used for statistical analyses - Hypothesis Testing, t-tests, etc.

Normalization on skewness and kurtosis of a dataset

Kernels for machine learning problems

An R package for causal discovery in heavy-tailed models

This is a homework I did in the Spring 2017. It involves conducting Chi Square Tests, Confidence Intervals, Kolmogorov-Smirnov Tests, and Shapiro-Wilk Normality Tests. It has problem numbers that are associated to problems in "Using R: Introductory Statistics".

Determined the best regression model which represents the data

Gaussian Navie Bayes Classifier was applied on IRIS dataset. Different types of normality tests were used to introduce the normality concepts.

This a project I did in the Spring of 2017 for the graduate course of Statistical Computing. This project includes T-Tests, Non-parametric Tests, Linear Regressions, Correlation Tests, Chi Square Tests, and tests for normality. This project also includes some basic graphing.

Estimate a suite of normalizing transformations, including a new adaptation of a technique based on ranks which can guarantee normally distributed transformed data if there are no ties: ordered quantile normalization (ORQ).

Linear Mixed-Effects Models for Non-Gaussian Repeated Measurement Data

An R-based workflow for conducting repeated measures ANOVA using the ez package, with data wrangling via tidyverse and visualization through ggplot2. Includes data import, transformation to long format, statistical analysis, and graphical summary.