Learning mathematical methods of data analysis in the language R.

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

A Rust crate for assessing the normality of a data sample.

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.

Compute a one-sample Z-test for a one-dimensional ndarray.

Compute a two-sample Z-test for two one-dimensional double-precision floating-point ndarrays.

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".

Compute a two-sample Z-test.

Normalization on skewness and kurtosis of a dataset

Compute a one-sample Z-test for a one-dimensional single-precision floating-point ndarray.

Kernels for machine learning problems

An R package for causal discovery in heavy-tailed models

Compute a one-sample Z-test for a strided array.

Determined the best regression model which represents the data

Compute a one-sample Z-test for a one-dimensional double-precision floating-point ndarray.

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.