Mastering R II: The Journey Continues

RLadies Rome Team

R Courses

Insurance Data

tidyverse

In this video, we dive into the features of R, for analysing insurance data, make visualizations, and look at first line of modeling, to eventually produce a report.

Published

September 22, 2023

Registered Attendees (50)

September 22, 2023 speaker is Federica Gazzelloni on behalf of R-Ladies Rome

Welcome to our second session, where we embark on an exciting journey into the world of R programming for data analysis, visualization, and modeling. R is a robust and versatile tool that’s tailor-made for statisticians, data analysts, and data scientists like yourself.

In this recording, we take a deep dive into the capabilities of R, using insurance data as our backdrop. We explore how to analyze this data, create visualizations, and take our first steps into the world of modeling, all leading to the production of insightful reports.

Whether you’re just starting with R or have some prior experience, this second crash course is designed to help you master the fundamentals and unleash the potential of this powerful language.

Feel free to enjoy the recording at your own pace. Pause, rewind, and replay as you delve into the fascinating world of data analysis with R.

If you have any questions or would like to share your assignments, please don’t hesitate to reach out to us at rome[at]rladies[dot]org.

For course materials, you can access them here:

Material of the course: –> Go to our Posit.Cloud Workspace
{CASdataset} collection of Insurance datasets: To install the package, simply use the following R code:

options(timeout = 6000)
install.packages("CASdatasets", 
                 repos = "http://cas.uqam.ca/pub/")
library(CASdataset)

We also recommended the book "Statistical Foundations of Actuarial Learning and its Applications" by M. V. Wüthrich and M. Merz for Actuarial investigations.

To get more familiar with Posit.Cloud, check out the Posit Cloud Essentials series here).

We used Posit.Cloud for this course, but if you prefer to install R directly on your machine, you can follow the instructions here.

For additional help and resources, don’t forget to explore the R4DS community at https://www.rfordatasci.com/ and read the R for Data Science - R4DS Book by Hadley Wickham [https://r4ds.had.co.nz/].

For those starting with R, have a look at our previous course: Mastering R: An Intensive Crash Course for Data Enthusiasts!

Enjoy your journey with R, and happy data analyzing!