blood test chi - Moozonian

GitHub Repo https://github.com/rajesh1624/Statistical-Relationship-Between-Blood-Pressure-and-Drug-Type-Chi-Square-Test-of-Independence-

rajesh1624/Statistical-Relationship-Between-Blood-Pressure-and-Drug-Type-Chi-Square-Test-of-Independence-

Conducted an end-to-end statistical analysis on the Drug200 dataset to determine whether a patient’s Blood Pressure (HIGH, LOW, NORMAL) is related to the type of drug prescribed. Performed exploratory analysis, contingency table creation, and hypothesis testing using the Chi-Square Test of Independence in Python.

GitHub Repo https://github.com/Khan-Aqsa/Studying-Association-of-Hypertension-with-Potential-Risk-Factors

Khan-Aqsa/Studying-Association-of-Hypertension-with-Potential-Risk-Factors

Objective: Study association of hypertension (systolic blood pressure) with risk factors (physical activity, salt intake, weight and tobacco use) by running chi square test, Kruskal Wallis Test and comparing means using NHANES data.

GitHub Repo https://github.com/shaikbashe1/child-health-monitoring-system-through-saliva

shaikbashe1/child-health-monitoring-system-through-saliva

Our project is a child-friendly saliva health monitoring system using pH sensors to detect saliva acidity levels. It provides real-time feedback with visuals, health advice, and tracks trends over time. It’s safe, non-invasive, and ideal for kids who avoid blood-based tests and injections

GitHub Repo https://github.com/Sturgeongit/Stat_Inference_Project

Sturgeongit/Stat_Inference_Project

In this group project, we used statistical inference methods such as t-test, chi-squared testing and regression to determine whethere the amount of CPK in blood tests was statistically significant WRT anemia

GitHub Repo https://github.com/guom815/SAS-Project----Infectious-Disease

guom815/SAS-Project----Infectious-Disease

Conducted a study on the impact of HIV status on elevated blood pressure in Johannesburg, South Africa; created tables for characteristics of participants, accounted for missing values, and identified potential confounders; employed Chi-square tests and regression modeling to estimate the risk ratio and the association of interest.

GitHub Repo https://github.com/hemisha11/Cardiometabolic-Risk-Factors-and-Smoking-Exposure-Analysis-in-SAS

hemisha11/Cardiometabolic-Risk-Factors-and-Smoking-Exposure-Analysis-in-SAS

Analyzed NHANES data in SAS by merging demographic, biomarker, body measure, and blood pressure datasets. Created derived variables (BMI, smoking exposure, age groups), performed t-tests, chi-square, correlations, and regressions, and generated tables/graphs to evaluate cardiometabolic risk factors.

GitHub Repo https://github.com/Thiyagesh25/healthcare-stats-project

Thiyagesh25/healthcare-stats-project

Statistical analysis on healthcare data (50 patients). Includes mean, median, std deviation, correlation, and chi-square test. Built with Python, Pandas, NumPy, Matplotlib, and SciPy to find insights between age, blood pressure, cholesterol, and recovery status.

GitHub Repo https://github.com/sathyaasampath-netizen/DataAnalytics---Cardiovascular-Diseases-Risk-Prediction-by-Clinical-Estimators

sathyaasampath-netizen/DataAnalytics---Cardiovascular-Diseases-Risk-Prediction-by-Clinical-Estimators

A data analytics project predicting cardiovascular disease risk using clinical indicators such as cholesterol, blood pressure, and exercise-induced angina. Applied statistical tests (t-test, logistic regression, chi-square) and built predictive models in Python to identify key risk factors

GitHub Repo https://github.com/ShivaniVellanki/ChiSquare-AnnovaAnalysis

ShivaniVellanki/ChiSquare-AnnovaAnalysis

The project uses Chi-Square and ANOVA in R to assess hypotheses across scenarios like blood type distribution and airline performance. It applies statistical tests to explore relationships and patterns, yielding insights into data significance.

GitHub Repo https://github.com/aaditya-pdgupta/regression_problem_in_biology

aaditya-pdgupta/regression_problem_in_biology

A least squares error fit is performed to different models and the best fit model using the chi-square test is selected, and the p-value of the selected model is calculated to data that was collected when various doses of a drug were injected into three animals, and the change in blood pressure for each animal was recorded.