Learning mathematical methods of data analysis in the language R.
A Rust crate for assessing the normality of a data sample.
Library for processing and extracting assets for the 3D/ADV engine
A series of Jupyter notebooks, to know about Machine Learning, its implementation, and identifying its best practices.
Testing effects of missing data on phylogenetic inferences
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.
Determined the best regression model which represents the data
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".
Kernels for machine learning problems
Normalization on skewness and kurtosis of a dataset
Compute a one-sample Z-test for a one-dimensional single-precision floating-point ndarray.
Code for "In search of 'normality': producing relevant counterfactual explanations for complex behaviors" (ACSOS 2026)
Compute a two-sample Z-test for two one-dimensional double-precision floating-point ndarrays.
Compute a one-sample Z-test for a strided array.
Compute a one-sample Z-test for a one-dimensional ndarray.
Gaussian Navie Bayes Classifier was applied on IRIS dataset. Different types of normality tests were used to introduce the normality concepts.
Regression analysis practical exam
To associate your repository with the normality topic, visit your repo's landing page and select "manage topics."