There are 0 repository under pvalues topic.
:bar_chart: Computation and processing of models' parameters
The MultipleTesting package offers common algorithms for p-value adjustment and combination and more…
Fast manhattenplots using ggplot2
A F&B manager wants to determine whether there is any significant difference in the diameter of the cutlet between two units. A randomly selected sample of cutlets was collected from both units and measured? Analyze the data and draw inferences at 5% significance level. Please state the assumptions and tests that you carried out to check validity of the assumptions. Cutlets.csv
A/B Testing for E-commerce website
a simple shiny app that perform statistical tests such as normal test, t-test, and chi-square test
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.
Machine Learning Project
Assignment-Simple-Linear-Regression-1. Q1) Delivery_time -> Predict delivery time using sorting time. 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, Feature Engineering, Correlation Analysis, Model Building.
Εxercises for Data Analysis course in Faculty of Engineering of Aristotle's University of Thessaloniki
:pill: AB Testing Between Versions
Multiple Linear Regression Dataset Name - 50_startups data.
Analyze A/B Test Results - Data Analyst Nanodegree with Udacity
This repository contains a python notebook that creates Table-1: baseline characteristics with p-values comparing two groups. Greatly helpful for clinical and biological studies. Can be used for manuscipts.
Multiple Regression model building with Sklearn and statsmodels and analysis of relevant predictors using P-values and VIF
This project is about conducting an A/B test for CityFit, where we compare the impact of two different submit button colors on increasing email sign-ups for an upcoming eCommerce launch.
To compute and plot significances (pvalues and asterisks) on bar graphs
Probability and Statistics in Data Science using Python
Regression Analysis with the BikeShare data.
The objective of this analysis was to explore potential correlations between player attributes (such as average age and weight across different positions) and key team performance metrics from the 2023 NFL season.
Hypothesis test practice
Live session poll done to conduct simple random sampling and hypothesis testing