Basic statistical modelling examples.
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Updated
Jun 17, 2024 - R
Basic statistical modelling examples.
Sub-package of spatstat containing functionality for parametric modelling and inference
Course materials for "Biostatistics: Case Studies"
Build and Tune Several Models
Analysis-of-variance time-series analysis based on the method of Schwarzenberg-Czerny (1989)
Analysis of Variance in R and Python
Analysis of Variance project. Analysis of Israel's employment bureaus data in the years 2010-2019 using statistical methods.
Using R, performed statistical analysis and data visualization of life expectancies of United States, Canada, and Mexico, using custom plots and data analysis.
🎓 Laboratory exercises from the course "Statistical Methods of Big Data" of the System Analysis of Uzhhorod National University.
A repository created to explore and understand Statistics through coding.
Zhao T, Alba C, Ryo H, et al “Park Visitation Dashboard,” In Spring 2021 Learning Factory Showcase.
An R project that investigates and visualizes the effect of sex and education on an individual's income level through the use of a full-factorial two-way ANOVA test and relevant post hoc significance tests conducted over a 2014 Pew Research Center dataset consisting of higher education attainment, gender, and income data.
The project involves sampling designs and summarizing data, maximum likelihood estimation of parameters, bootstrap, parametric and non-parametric inference, the analysis of variance, linear least squares, categorical data, elements of the decision theory and bayesian inference.
This project is a Pinball designed experiment to determine the effect of different types of ball on the distance in which the ball is thrown. After gathering the data from thrown balls, a hypothesis test was done on the sample mean of each treatment (thrown ball) in a completely randomized design with an alpha around 0.05.
A Data Science Portfolio for potentially interested employers and recruiters.
A tool for the analysis of datasets obtained by performing experiments according to a Design of Experiments (DoE) approach.
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