Using Python to work up a Design of Experiments

My this project repository focused on hypothesis testing involving T-test, Chi-square test, Binomial Test, ANOVA, Sample Size Determination with scipy, statmodels modules.

Analysing the results of an A/B test run for 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.

Exploration of descriptive and inferential statistical methods using Python and Jupyter Notebook.

Tried to understand whether the company should implement a new page or keep the old page with some statistical techniques.

Created model using Linear regression to predict variables impacting demand.

Model created using Logistic Regression to identify potential leads

Tutorials for BSE classes.

This repo contains files for the blog post about conjoint analysis

Crop yield Forecasting on the basis of meteorological predictions using some Time series & ML models

Time Series forecasting using Seasonal ARIMA. Applied statistical tests like Augmented Dickey–Fuller test to check stationary of series. Checked ACF ,PACF plots. Transformed series to make it stationary

Multiple Linear Regression Study to predict King County House Sale Prices

Explorer, nettoyer et analyser pour effectuer une modélisation des données

Udacity Data Analyst Nanodegree - Project III

Multivariate time series Vector Autoregression Model (VAR) on real world GDP and DPI (and some other indexes). Bayesian Structured Time Series (BSTS).

Used libraries and functions as follows:

ExcelR Data Science Assignment No 1

ExcelR Data Science Assignment No 2

ExcelR Data Science Assignment No 3