Detailed analysis of penguin dataset; K-means clustering and classification models built to predicate penguin features for superior penguin management

This project analyzes a heart disease dataset to explore the relationship between cholesterol, heart rate, and chest pain type. It includes normality tests, outlier detection, correlation analysis, MANOVA, post-hoc tests, and VIF analysis, with visualizations using histograms, heatmaps, and boxplots.

This project explores Tukey’s Honest Significant Difference test as a robust statistical method for comparing group means after conducting ANOVA. In real-world data analysis, we often need to determine not just whether groups are different, but which specific groups differ

R package with a collection of useful functions for lm, Tukey-HSD, etc.

Projekt studencki

📉 Statistical Analysis

It is a method that allows analyzing the differences among group means in a given sample. ANOVA is a collection of statistical models and their associated estimation procedures like variation within and between groups. It is used to study the modification of mþ as the average of the studied phenomenon Y (quantitative/continuous/dependent variabl…

A repository created to explore and understand Statistics through coding.

An R repository featuring from-scratch implementations of one-way and two-way ANOVA, along with Tukey's HSD test.

Very detailed exploratory data analysis is executed on the dataset. Univariate and bivariate analysis using ANOVA and Chi-Squared Test between continuous and categorical variables are explored to find out the relationship between input variables and the output target 'revenue'.

OFA Tool

📊 Upload CSV/Excel files to generate boxplots, run ANOVA, and auto-calculate Tukey HSD — no coding needed.

For this Project, I first applied an analysis of variance (ANOVA) model to the Pymaceutical dataset and then did a post-hoc analysis of the results by using Tukey Honest Significant Difference (HSD) to determine which drug treatments in the dataset significantly reduce tumor volume and metastasis. I then wrote a summary of my findings.

This project uses ANOVA in Python to analyze how diamond color and cut affect pricing. By testing for statistical significance and running post hoc comparisons, it reveals key pricing patterns. Built with pandas, statsmodels, and Seaborn, the findings help inform diamond valuation and purchasing decisions.

Using binom_test, ttest_1samp, ttest_ind, f_oneway, pairwise_tukeyhsd, chi2_contingency to investigate some data from a sample of patients who were evaluated for heart disease.

This project implements a Compact Letter Display (CLD) system in Python to simplify Tukey HSD results by assigning letters to groups

It compares the pair of mean tensile strength having significantly equal means using tukey cramer test. It will further help us to improve our decisions based on this insight at the production and design side.

Ruby method that removes extreme data points from an array using Tukey's method

Statistical Analysis on COVID-19 data to examine the statistical significance across the different regions.