Machine learning for beginner(Data Science enthusiast)

Case Studies and Projects in Machine Learning/EDA/DL

A 30+ node flowchart for selecting the right statistical test for evaluating experimental data.

This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD).

A friendly, automated chi-square test function which takes care of post-hoc tests and multiple comparisons.

This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD) with MRI data.

Chi-Squared For Feature Selection using SelectKBest

"A set of Jupyter Notebooks on feature selection methods in Python for machine learning. It covers techniques like constant feature removal, correlation analysis, information gain, chi-square testing, univariate selection, and feature importance, with datasets included for practical application.

about statistical techniques for Data Science

Leveraging data-driven approaches to mitigate Credit Risk and optimize financial strategies in the banking sector.

Lean Six Sigma with Python — Chi-Squared Test

Adapted chi-squared and CMH test to evolve and resequenced data. Includes drift and pool sequencing variance in the tests

Wesleyan University

No description provided.

Polycystic Ovary Syndrome (PCOS) is a widespread pathology that affects many aspects of women's health, with long-term consequences beyond the reproductive age. The wide variety of clinical referrals, as well as the lack of internationally accepted diagnostic procedures, have had a significant impact on making it difficult to determine the exact etiology of the disease. The exact histology of PCOS is not yet clear. It is therefore a multifaceted study, which shares genetic and environmental factors. The aim of this project is to analyse simple factors (height, weight, lifestyle changes, etc.) and complex (imbalances of bio hormones and chemicals such as insulin, vitamin D, etc.) factors that contribute to the development of the disease. The data we used for our project was published in Kaggle, written by Prasoon Kottarathil, called Polycystic ovary syndrome (PCOS) in 2020. This database contains records of 543 PCOS patients tested on the basis of 40 parameters. For this, we have used Machine Learning techniques such as Logistic Regression, Decision Trees, SVMs, Random Forests, etc, A detailed analysis of all the items made using graphs and programs and prediction using Machine Learning Models helped us to identify the most important indicators for the same.

All type of calculators like Cuboid (4D), Binning, Chi-square test, Red-black tree, Binary search tree, Longest Common Sub Sequence, Master Theorm, Heap Sort, Decision Theory at one place ✨

The code build a correlation like heat but using chi-square test for catagorical variables. Python and R have built in libraries for producing heatmap for correlation test but there is no such library to produce heat map for chi-square test of association.

Notes on statistical inference made for learning statistics for data scientists

Evaluating the impact of adding 360-degree product videos feature on the product page on sales for an E-Commerce Platform.

Examples of using the test statistics to test hypotheses

Shiny interface for growth model fit

a simple shiny app that perform statistical tests such as normal test, t-test, and chi-square test

Hypothesis Testing in Data Analysis This repository contains a Jupyter Notebook demonstrating various hypothesis testing techniques using Python. It covers statistical tests such as t-tests, ANOVA, chi-square, and non-parametric methods, with real-world examples and visualizations.

Package provides python implementation of statistical inference engine

IU Lessons

A collection of real-world business problems and their solutions from ‘Business Statistics: A First Course’ by Dr. P.K. Viswanathan, designed to enhance understanding of key statistical concepts through practical application. Ideal for students and professionals looking to apply statistical methods to real business scenarios.

chi-square test within the Montana Library case study.

The project aims to build a Species Distribution Model for the frog species - "Litoria Fallax" across Australia using TerraClimate variables.

This repository contains four different hypothesis testing projects, analyzing real-world data to validate assumptions and drive data-driven decisions. Each project applies statistical tests (e.g., t-tests, chi-square, ANOVA) to uncover insights and support business strategies. Built with Python, Pandas, SciPy, and Statsmodels. 🚀

Generate and download free synthetic datasets instantly! A Streamlit app with built-in statistical validation tools like Chi-Square and Mutual Information.