There are three R files, each one consist on a main phase of the project, these are: data preparation, data cleaning and data analysis. This file explains the content of each one and the result. To ...
Analyzed the relationship between BMI and life satisfaction using data from the CCHS. Explored the moderating effect of diabetes and accounted for nonlinearity in the relationship. Built multiple ...
One of the first steps in any data analysis project is to clean and manipulate the data to suit your needs. R offers many functions and packages for this purpose, such as dplyr, tidyr, stringr ...
R offers a wide range of packages to assist with risk analysis, including data import, cleaning, exploration, modeling, testing, and reporting. Notable packages for this purpose include tidyverse ...
apply basic R functions for twin-focused data analysis and visualization, and (4) translate the implementation of a basic ACE model between a structural equation model and an OpenMx model ...
In this module, we will learn how to diagnose issues with the fit of a linear regression model. In particular, we will use formal tests and visualizations to decide whether a linear model is ...