Deep R Programming (Open-Access Textbook)

An ongoing project for an online toolkit to analyze online controlled experiments. Its mission: To make inferential statistics accessible for everyone.

This repository contains the project for the course Statistics and Probability 1 from the Faculty of Engineering and Basic Sciences. The main focus of the project is the application of probability distributions such as normal, exponential, gamma, Poisson, and binomial distributions to solve real-world problems.

Welcome to the U.S. Census at School Random Sampler This facility provides random data samples selected from individuals in the U.S. Census at School population that meet your selected characteristics.

This project uses statistical hypothesis testing to examine the link between cholesterol and fasting blood sugar levels with heart disease. One-sample t-tests and binomial tests are applied to assess whether these health metrics significantly differ from expected values, focusing on their association with heart disease.

The Poisson Distribution models the number of events that occur within a specified time frame, such as years. Since the volume of incoming calls fluctuates from year to year, this distribution aids in determining whether the call data aligns with a Poisson process or if external factors are affecting the call volume.

The Poisson distribution is a useful model for analyzing product defects, helping to estimate expected defect rates, their variability, and the likelihood of extreme cases. This understanding aids in enhancing quality control processes and minimizing defects.

This portfolio features all the Data Science and Machine Learning projects I have completed for academic, self-learning and hobby purposes. Additionally, it is updated regularly.

This is a repository containing the notes on statistics and probability for Data Science from basics to Advance

This repo contains all two problem set solutions of Applied Regression Course.

A tool for visualizing the coefficients of various regression models, taking into account empirical data distributions.

Explore "Statistics" and "Probability Theory" Concepts and Their Implementations in "Python"

Summary of Assignment Two from the first semester of the MSc in Data Analytics program. This repository contains the CA2 assignment guidelines from the college and my submission. To see all original commits and progress, please visit the original repository using the link below.

All Statistics concepts

This repository contains a collection of Jupyter Notebooks for conducting Exploratory Data Analysis (EDA) and Statistical Analysis on various datasets.

collection of Jupyter Notebooks in both English and Spanish, dedicated to performing data quality analysis using the R programming language

The Following problems showcase different Statistical Methods used for Decision Making. The purpose of this project is to experiment and execute statistical methods, which are required to conduct data analysis, derive insights and inferences and arrive at business decisions.

Excel calculating the probability distribution simulated data

Book of Demythologize Durbin-Watson Test Statistic | Correct the critical values of DW statistic

The R code authored below goes through cleaning, visualizing and modeling data as well as some useful simulations for concepts in Research Statistics and markdown reports. Some code is shell code for the participant to complete; some are examples of the completed shell code. For more advanced R methods, see Dashboards_DataScience repo