npm package to run Chi-Squared tests on numerical arrays.

Examples of using the test statistics to test hypotheses

ChiSeL: Graph Similarity Search using Chi-Squared Statistics in Large Probabilistic Graphs

A hub that contains notebooks that perform elementary descriptive statistics of populations and samples and demonstrates 3 hypothesis tests- Welch t-test, Correlation, and Chi-square test. It shows how to run them in python and understand the results

Comprehensive statistical analysis project in R covering 10 exercises: data visualization (ggplot2), probability distributions, hypothesis testing, MLE, CLT, confidence intervals, and goodness-of-fit tests. Academic project for IST's Probability & Statistics course.

The aim is to develop an ML- based predictive classification model (logistic regression & decision trees) to predict which hotel booking is likely to be canceled. This is done by analysing different attributes of customer's booking details. Being able to predict accurately in advance if a booking is likely to be canceled will help formulate prof…

This project explores the Framingham Heart disease dataset with the objective to predict its risk in 10 years. Various methods for handling missing values and outliers are explored as iterations. After analysing the dataset, important and necessary features are selected. Seven ML models are implemented, with evaluation on the basis of Test Recall.

Effort here is to identify important features in relation to our target variable using multiple Correlation methods based on data type. Feature selection is important for ML models to avoid 'curse of dimensionality' but for this dataset we will be using it build our intution that benefits our later EDA effort

Исследование влияния характеристик клиентов, которых страховая компания обслуживает, на размер страховых выплат

End-to-End Python scalable forensic accounting toolkit implementing Benford's Law analysis for FTSE financial data. Delivers automated anomaly detection with Chi-Squared/MAD testing, comprehensive validation pipelines, and risk-based prioritization of investigative resources. Replicates Ausloos et al.'s (2025) methodology with full reproducibility.

Tester for basic statistical tests

Statistics Projects for Intro to Statistics, and Probability & Statistics courses at Ashoka

We’ll work with a dataset of Jeopardy questions to figure out some patterns in the questions that could help one win.

Statistical project based on the Netflix user-base dataset from Kaggle

Analyze Data with Python | Hypothesis Testing with Scipy

Masters Project: Logistic Regression Analysis, Comparing the Completion of Latent Tuberculosis Therapy of HIV-Coinfected Individuals and Other Chronic High Risk Groups

I will use Excel to perform statistical analysis for the user study results in this project. Specifically, I will use the Real Statistics Resource Pack for performing the analysis.

In this project, we are gaining insights about the show's questions.

📊 Test financial data for conformity to Benford's Law using this scalable framework for reliable analysis and insights.