OLAP (Online Analytical Processing) is a very common way to analyze raw transaction data by aggregating along different combinations of dimensions. This is a...
Cox regression model is widely used in medical research to assess the effect of several risk factors on the survival time of patients. The {ggforest} function from {survminer} Paket easily creates a forest plot of its model estimates.
This lesson is designed for librarians and library professionals with little or no prior experience with R to be more acquainted with the programming language. Having a level of familiarity with R is beneficial in assisting users with requests regarding the cleaning, formatting, and visualization with data along for librarians and library professionals themselves when it comes to data they intend to use and analyze for their internal workflows.
Learners will become familiar with both R, R Studio software environment, and the Tidyverse. The R Studio environment allows one to run their code and see the immediate results of one’s code separate panels. While R originally started as a being a statistical programming language, R is used for various applications such as data visualization, deploying of web applications, and creating reproducible documentation. Given the extensive applications of R, we will solely be focusing on importing, cleaning, and visualizing data.
En lugar de presentar todos los pormenores de R de manera lineal, se irán presentando distintos aspectos de R conforme se vayan necesitando; es decir, no vamos a presentar R como un lenguaje de programación sino como una herramienta para hacer análisis estadísticos.