Machine learning for beginner(Data Science enthusiast)

This repository is created for storing the components of Statistical Tests of One Pop, Two Pops and Three or more pops using Python.

Code and data for the paper "Critical Values Robust to P-hacking"

Examples of using the test statistics to test hypotheses

This repository contains all of the statistical Inference-related projects I've worked on. The projects are part of the graduate course at the University of Tehran.

This repository contains introductory notebooks for basic hypothesis testing problems.

Large sample tests for Means and proportions based on single and two samples using R

working to understand the results of an A/B test run by an e-commerce website. The company has developed a new web page in order to try and increase the number of users who "convert," meaning the number of users who decide to pay for the company's product.

Analysis of Romantic Relationships using Statistical Modeling

Collection of Jupyter Notebooks covering fundamental concepts such as hypothesis testing, statistical power, and various tests for one or two samples, as well as variance. Most functions and test are written from scratch for educational purposes.

Performed rigorous preprocessing, and data cleaning, and conducted exploratory data analysis to identify trends, patterns, and outliers, leading to valuable insights. Employed various statistical methods concepts to get insights about the data for prediction.

Homeworks and R projects for the course Foundations of Data Science

The data relates to several user actions or interests recorded on two variants of landing pages for an online news portal. The objective is to analyse these interests by performing statistical analyses to determine if one variant is more effective based on chosen metrics (A/B testing).

This repo contains various Statistics techniques like descriptive_Statistics including Central tendency, CLT, Z_Score and inferential statistics etc..

E-news Express, an online news portal, aims to expand its business by acquiring new subscribers. This python based project performs EDA, data visualization and conducts a no of statistical tests to determine key business insights: in particular whether the new landing page can get greater viewership duration and subscriber conversion

This repository has been created to link my statistical testing assignments and independent studies for Thinkful as I navigate thru the Data Analytics Immersion program from October 2020 - January 2021.

Analyse efficacy of your own methods for calculating confidence interval

My first classification problem solved with logistic regression.

About Performed A/B test and help the company decide whether they should implement the new web page, keep the old page, or run the experiment longer.

The project explores a range of methods, including both statistical analysis, traditional machine learning and deep learning approaches to anomaly detection a critical aspect of data science and machine learning, with a specific application to the detection of credit card fraud detection and prevention.