pvalue

MATLAB special heatmap, plot heatmaps of various shapes, triangular heatmaps, and add dendrograms and significance labels.

BoolTest - polynomial randomness tester

Supervised Machine Learning project with KNN, decision tree, random forest and adaboost algorithms

A comprehensive collection of statistical concepts, probability, hypothesis testing, and data analysis techniques for Data Science using Python.

EDA - Pre processing | Feature Engineering

Tutorials for BSE classes.

In this project, statistical analysis approach is employed to decide what hypothesis to be rejected. Scipy Stat library is used to find the pvalue that will determine if Hypothesis Null should or should not be rejected.

Used libraries and functions as follows:

Informal suite of functions to calculate simple power calculations via p-value simulation.

To compute and plot significances (pvalues and asterisks) on bar graphs

A complete Python project demonstrating parametric and non-parametric hypothesis testing using a real-world Car Dataset, with clear explanations, visualizations, and practical insights

Code written in R for the p value calculation of the Barnard test, Boschloo test and modified Boschloo test for 2x3 designs

Regression Analysis with the BikeShare data.

Analyzing impact of the coating on golf ball

Population_Pyramid_France_2017

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.

Now, this repository contains the links of the videos that I have recorded for the training of this software. Also, the files have been placed in order to familiarize Statistics enthusiasts with some of the statistical concepts used in this software.

Assignment-04-Simple-Linear-Regression-2. Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.