10 Days of Statistics Challenges at HackerRank

A MATLAB project which applies the central limit theorem on PDFs and CDFs of different probability distributions.

about statistical techniques for Data Science

Exercises solved for the Practical Statistics Module of Udacity's DAND: assignments and practice problems

Machine Learning Code Implementations in Python

Demonstrate central limit theorem (CLT)

EPS course projects

Topics in Probability Theory and Stochastic Processes

Comprehensive notes and solved problem sets from Casella-Berger: Statistical Inference (Chapters 1-5), covering foundational concepts in probability and distribution theory. Topics include random variables, probability distributions, expectation, and limit theorems, essential for applications in machine learning, AI, and robotics.

Exercise solution to the Probability Theory course

Exploring CLT with Python

Data Science Statistics Interview Questions

Central Limit Theorem for Process Improvement with Python

Business Case: Walmart - Confidence Interval and CLT

Analysing customer purchasing behaviour against the customer's gender and various other factors to help the business make better decisions.

Data Analysis Course (EE 201), IIT Dharwad

CSE 569, Fall 2019 Fundamentals of Statistical Learning Course at ASU

This repository contains the solutions to HackerRank's 10 Days of Statistics.

🎲 Demonstration of the Central Limit Theorem & the Law of Large Numbers

Analyze Walmart Black Friday purchase data to understand customer spending patterns by gender, marital status, and age using Confidence Intervals and the Central Limit Theorem (CLT). Includes EDA, visualization, hypothesis testing, and actionable business insights.

Projects for the Intelligent Systems course

Run the CLT Shiny app : https://datatrigger.shinyapps.io/CLT_Visualization/

Project for the Data Science PhD course of Probability

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.

Monte Carlo Simulation of Exponential Distribution and Inferential Analysis of Tooth Dataset

No description provided.

Scripts to visualize the central limit theorem in action.

The idea is to write a piece of Python code to check that the Central Limit Theorem works.

compact, hand-written notes to learn statistics — from probability distributions to inference and the Central Limit Theorem.

10 Days of Statistics Hackerrank Solutions