2022 CAS Virtual Workshop - Introduction to R

Event Details

-
Thursdays, 1:30 PM - 3:00 PM (ET)

Held in Microsoft Teams

About This Event

This series of six lectures will give the attendee a broad introduction to the features of the R programming language most useful to actuaries, with the objective of preparing attendees to apply what they've learned in each lecture immediately in their work.

Attendance is limited to 35 participants, individual registrations only. Group registrations are not permitted.

Learning Objectives

Each week will focus on a different aspect of using R in actuarial work. The lectures will include real examples that can be adapted for use immediately following each lecture to give the attendees a starting point for using R. At the end of the six lectures, attendees will have been exposed to a broad range of topics:

  • Using R studio for R programming
  • Reading data into the R environment from a variety of sources
  • Manipulating and visualizing data using packages like dplyr and ggplot2
  • Fitting, evaluating, and comparing linear models, including GLMs
  • Using R for curve fitting, calculating limited expected values, etc., with help from the actuar package
  • Writing reports using Rmarkdown
Event information

Casualty Actuarial Society's Envisioned Future

The CAS will be recognized globally as the premier organization in advancing the practice and application of casualty actuarial science and educating professionals in general insurance, including property-casualty and similar risk exposure.

Continuing Education Credits

The CAS Continuing Education Policy applies to all ACAS and FCAS members who provide actuarial services. Actuarial services are defined in the CAS Code of Professional Conduct as "professional services provided to a Principal by an individual acting in the capacity of an actuary. Such services include the rendering of advice, recommendations, findings or opinions based upon actuarial considerations". Members who are or could be subject to the continuing education requirements of a national actuarial organization can meet the requirements of the CAS Continuing Education Policy by satisfying the continuing education requirements established by a national actuarial organization recognized by the Policy.
 
This activity may qualify for up to 10.8 CE credits for the 2022 Virtual R Workshop for CAS members. Participants should claim credit commensurate with the extent of their participation in the activity. CAS members earn 1 CE credit per 50 minutes of educational session time, not to include breaks or lunch.
 
Note: The amount of CE credit that can be earned for participating in this activity must be assessed by the individual attendee. It also may be different for individuals who are subject to the requirements of organizations other than the American Academy of Actuaries.

Speaker Opinions

The opinions expressed by speakers at this event are their own and do not necessarily reflect the opinions of the CAS.

Contact Us 

For more information on content, please contact Wendy Ponce, Professional Education Coordinator, at wponce@casact.org.  
 
For more information on course logistics or attendee registration, please contact Leanne Wieczorek, Manager Meeting Services at lwieczorek@casact.org.

For more information on other CAS opportunities or regarding administrative policies such as complaints and refunds, please contact the CAS Office at (703) 276-3100 or office@casact.org.

    Registration information

    Limit up to 35 participants. Group registrations are not permitted.

    Registration Type Early (On/Before Oct. 6) Late (On/After Oct. 7)
    Member/Subscriber/Candidate/iCAS Member $650 $750
    Non-Member $850 $950

    Cancellations/Refunds

    Registrations fees will be refunded for cancellations received in writing at the CAS Office via email, refund@casact.org, by October 13, 2022 less a $200 processing fee.

    Speakers

    Brian Fannin has been an actuary for over 20 years. The data lack sufficient credibility for him to give a more precise estimate. Brian has been an Associate of the CAS since 2002 and a Certified Specialist in Predictive Analytics (CSPA) since 2017. He has worked in a variety of roles in commercial insurance, both primary and excess, here in the US as well as Europe, London and Asia. An early proponent of R, he has taught various workshops and seminars for the CAS, Actex and insurance clients. He is the author of the book “R for Actuaries and Data Scientists with Applications to Insurance”, published by Actex. He joined the staff of the CAS in March of 2018 as a Research Actuary. His focus is to enable CAS committees and research partners to work efficiently in developing relevant, practical content.

    Adam L. Rich is an actuary, data scientist, and computer programmer with nearly 20 years experience.  He currently works for Beazley Group in Farmington, CT, and leads many underwriting innovation research and implementation projects.  Adam has been using R and teaching it to others for over 10 years.

     

    Schedule

    Pre-Work

    • Install R, RStudio. Please access these helpful links.
    • Read the raw book.
    • Complete a few basic exercises.
    Days Date Activity Time
    Sess 1 - Thu Oct 27

    Introduction to R

    • Using Rstudio
    • Introduction to basic R operations and data types
    • Getting data into R for further analysis
    • Exporting data
    1:30 - 3:00 PM
    90 min lecture
    Sess 2 - Thu Nov 3

    Using dplyr to get a handle on your data

    • Reshaping, and other manipulation
    • Data aggregation
    • Joining data sets
    1:30 - 3:00 PM
    90 min lecture
    Sess 3 - Thu Nov 10

    Data Visualization and RMarkdown

    • ggplot2 package for creating beautiful visualizations
    • Customizing visualizations
    • rmarkdown package for writing reports easily
    1:30 - 3:00 PM
    90 min lecture
    Sess 4 - Thu Nov 17

    Classical Linear Modeling and GLMs

    • Prepare data for modeling
    • Fit models
    • Diagnose, evaluate and compare different models
    • Logistic and count regression
    • Using different error families and offsets in GLMs
    1:30 - 3:00 PM
    90 min lecture
    Sess 5 - Thu Dec 1

    Statistical Distributions

    • Using and creating different distributions in R
    • Sampling or simulating from those distributions
    • Curve fitting and goodness-of-fit testing
    • Using the actuar and fitdistr packages
    1:30 - 3:00 PM
    90 min lecture
    Sess 6 - Thu Dec 8

    Tree-based Models

    • Decision trees
    • Random forests
    • Boosted trees
    1:30 - 3:00 PM
    90 min lecture

     

    Schedule

    Pre-Work

    • Install R, RStudio. Please access these helpful links.
    • Read the raw book.
    • Complete a few basic exercises.
    Days Date Activity Time
    Sess 1 - Thu Oct 27

    Introduction to R

    • Using Rstudio
    • Introduction to basic R operations and data types
    • Getting data into R for further analysis
    • Exporting data
    1:30 - 3:00 PM
    90 min lecture
    Sess 2 - Thu Nov 3

    Using dplyr to get a handle on your data

    • Reshaping, and other manipulation
    • Data aggregation
    • Joining data sets
    1:30 - 3:00 PM
    90 min lecture
    Sess 3 - Thu Nov 10

    Data Visualization and RMarkdown

    • ggplot2 package for creating beautiful visualizations
    • Customizing visualizations
    • rmarkdown package for writing reports easily
    1:30 - 3:00 PM
    90 min lecture
    Sess 4 - Thu Nov 17

    Classical Linear Modeling and GLMs

    • Prepare data for modeling
    • Fit models
    • Diagnose, evaluate and compare different models
    • Logistic and count regression
    • Using different error families and offsets in GLMs
    1:30 - 3:00 PM
    90 min lecture
    Sess 5 - Thu Dec 1

    Statistical Distributions

    • Using and creating different distributions in R
    • Sampling or simulating from those distributions
    • Curve fitting and goodness-of-fit testing
    • Using the actuar and fitdistr packages
    1:30 - 3:00 PM
    90 min lecture
    Sess 6 - Thu Dec 8

    Tree-based Models

    • Decision trees
    • Random forests
    • Boosted trees
    1:30 - 3:00 PM
    90 min lecture