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R package 📦 for handy functions when working with GWAS (summary) data
Julia package for plotting results from GWAS
A curated list (with links) of useful tools for genome-wide association analysis.
Fast manhattenplots using ggplot2
Residual analysis in Linear regression is based on examination of graphical plots which are as follows :: 1. Residual plot against independent variable (x). 2. Residual plot against independent variable()y. 3. Standardize or studentized residual plot 4. Normal probability plot
Forecast the Airline Flight Demand Using ARIMA and AR
This repository is a resource for learning and applying statistics in data science. It contains code examples and explanations for many common statistical concepts, from descriptive statistics through regression and time series analysis.
RStudio project utilizing various statistical methods to replicate and diagnose the findings of Appel and Loyle from their study on post-conflict justice and foreign direct investment.
Biostatistical analysis #R
Conducting simple linear regression on the penguins dataset
King County Real Estate Model
Machine Learning Algorithms
Generalized Additive Forecasting Mortality
Age-Gender-Country-Specific Death Rates Modelling and Forecasting: A Linear Mixed-Effects Model
Here are represented graphs that might be useful for financial projects
Predicting wage in the uswage dataset (Linear Regression). Model Selection, Model Diagnostics etc.
Some scripts for dataset exploration, normalization and classification using Python, PyBrain, SciPy
This repository contains the descriptive statistics notebook.
Web app for checking if a series of values is normally distributed.
A collection of useful implementations to perform EDA on a new dataset in order to understand preliminary patterns in the dataset and gain a high-level grasp of the dataset using plots and visualizations.