r-coding

name	r-coding
description	Solve R-based actuarial exam questions (e.g. CS1B, CS2B) using R scripts

R Coding Skill

You are solving an R-based actuarial exam paper (e.g. CS1B, CS2B). These papers typically provide data files (e.g. .RData or .csv) and expect candidates to write R code to perform statistical analysis and output results.

Overview

Your workflow is:

1. Identify data files (usually .RData or .csv in exams/<SUBJECT>/<SITTING>/)
2. Write R scripts for each question
3. Run the scripts (if R is installed) to produce numerical answers
4. Save outputs (plots, console output)
5. Document your code and results in attempt.md

Step 1 — Identify Data

Check the exam directory exams/<SUBJECT>/<SITTING>/ for data files.

• .RData: Load using load("path/to/file.RData")
• .csv: Load using read.csv("path/to/file.csv")
• .txt: Load using read.table("path/to/file.txt")

Step 2 — Write R Scripts

For each question, write a standalone R script that:

1. Loads the data
2. Performs the required analysis (summary stats, GLMs, time series, etc.)
3. Prints the results
4. Saves any required plots to results/<MODEL>/<SUBJECT>/<SITTING>/

Template for an R script

# ── Load Data ───────────────────────────────────────────────────
# Adjust path as needed - use absolute paths or relative to execution dict
load("exams/<SUBJECT>/<SITTING>/data.RData")

# ── Perform Analysis ────────────────────────────────────────────
# Example: Linear Model
model <- lm(Y ~ X, data = my_data)
summary(model)

# Example: Plotting
png("results/<MODEL>/<SUBJECT>/<SITTING>/q1_plot.png")
plot(model)
dev.off()

# ── Print Results ───────────────────────────────────────────────
print(summary(model))
# Print specific values if needed
cat("Adj R-squared:", summary(model)$adj.r.squared, "\n")

Step 3 — Run Scripts

Run the script using Rscript and capture the output:

Rscript results/<MODEL>/<SUBJECT>/<SITTING>/q1_solution.R > results/<MODEL>/<SUBJECT>/<SITTING>/q1_output.txt

Note: If Rscript is not available, you should still write the correct R code in the script file and include it in your attempt, but explicitly state that you could not run it to verify the output.

Step 4 — Document in attempt.md

In attempt.md:

1. Show the R code used.
2. Paste the output (from the text file or your own analysis if unable to run).
3. Embed plots using markdown image syntax: ![Q1 Plot](q1_plot.png).
4. Interpret the results as required by the question (e.g. "The p-value is < 0.05, so we reject H0...").

Common R Tasks for Actuarial Exams

• Linear Regression: lm(y ~ x)
• GLMs: glm(y ~ x, family = poisson)
• Time Series: arima(x, order = c(1,0,1))
• Survival Analysis: survfit(Surv(time, event) ~ 1)
• Bootstrap: Use sample()
• Simulation: rnorm(), rpois(), etc.