chi-square-test

28101991SUNNY/BusinessCase_Data_Exploration-

Case Studies and Projects in Machine Learning/EDA/DL

edaaydinea/OP1-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease

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

pleonova/stat-tests

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

edaaydinea/OP2-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease-with-MRI-data

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.

neuhofmo/chisq_test_wrapper

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

bhattbhavesh91/chi-squared-feature-selection-selectkbest

Chi-Squared For Feature Selection using SelectKBest

28101991SUNNY/Statistics_study

about statistical techniques for Data Science

tanvirnwu/Feature-Selection--Python

"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.

shafqaatahmad/chisquare-test-heatmap

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.

Gkontopodis/Data-Analysis-Tools

Wesleyan University

JonasVasconcelos/FiShiny

Shiny interface for growth model fit

MartaPelizzola/ACER

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

nrsharip/test-statistics

Examples of using the test statistics to test hypotheses

rebeccak1/pricing-test

samirsaci/lss-chi-squared

Lean Six Sigma with Python — Chi-Squared Test

Shivangi1Raghav/PCOSprediction

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.

SujalXplores/Mega-Calculator

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 ✨

chen0040/pysie

Package provides python implementation of statistical inference engine

jessicaageorge5/radiation_oncology_analysis

[Survival Analytics] Working with Dr. Surbhi Grover MD, MPH evaluating survival outcomes, treatment, and survivorship for a cervical cancer cohort with or without HIV co-infection in Botswana, Africa using methods rooted in statistics.

mahdibaghbanzadeh/statistical_tests

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

RaghuveerRao/Statistics-Inference

Notes on statistical inference made for learning statistics for data scientists

AdammGreen/R-Marketing-Analysis

Here I did an analysis of a survey taken on cell based meat and processed it using R to find correlations and make some assumptions on the data.

afidas/churn-behavior

Customer churn analysis using EDA and confirmed by Chi-square hypothesis testing.

al6133/Random_Number_Generators

Implementing Unif(0,1) Pseudo Random Generators & performing Statistical Tests on them

briggyx/bank_marketing_analysis

This project analyzes a Portuguese bank's term deposit marketing campaigns, uncovering key factors and client profiles to optimize marketing strategies and enhance the bank's lending pool and revenues.

c-susan/datasci_5_statistics

HHA507 / Data Science / Assignment 5 / Inferential Statistics

Latiifff/Statistical_Analysis

This repository contains statistical analyses conducted on various datasets related to medical and health factors. The analyses include Spearman correlation, Chi-square test, and Linear Regression to explore relationships and predictive models related to heart attacks and other medical conditions.

LinaYorda/Chi-Square-Test-on-university-website

chi-square test within the Montana Library case study.

mahnoorsheikh16/Optimizing-Supply-Chain-Efficiency-with-Geospatial-Data

Leveraged historical geospatial data to forecast weather patterns, optimize delivery times and methods to improve efficiency and reduce costs.

nikitaprasad21/Credit-Risk-Modeling

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

Ohm-Rajpal/FinalProject

Stats HW chat bot that solves chi-square problems involving goodness of fit, homogeneity, or independence

PatilNi3/TABLES-IN-STATISTICS

In Statistics, various tables used to reference critical values for different distributions and tests.

vanylush/Diabetes_Prediction_Model

Embark on a journey of data-driven insights with our diabetes research project. Leveraging Python's pandas, matplotlib, and scikit-learn, we preprocess, visualize, and analyze 330 health features. Employing logistic regression, decision trees, KNN, and SVM, we predict diabetes with precision.

vrinda1997/Local-Frog-Discovery-Tool

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

ZL63388/ab-testing-codes

This repository is a collection of basic code templates for A/B Testing. All codes I am sharing are from the practical exercises I did from the Data Science Infinity Program.