Probability introduction

Last reviewed May 28, 2026 Content v20260528

Track mode: server_script
Means: Server runner
Reading: ~1 min
Level: intermediate

This lesson

An orientation to the R track—how the compiled playground works, core vocabulary, and what you will practice next.

You need a clear map of the R track so vectors, data frames, factors, and the tidyverse mindset do not feel like magic.

You will apply Probability introduction in contexts like: Research pipelines, Shiny dashboards, and statistical reporting.

Write R in the editor and click Run on server—the dev runner executes with Rscript; use print() or cat() and base R in playground snippets (tidyverse locally; LEARNING_RUNNER_ENABLED=true). Also read the interview prep blocks.

After basic programming and ideally SQL—pair with Python for ML-heavy roles or stay in R for stats and research pipelines.

R includes distributions via d*, p*, q*, r* functions—density, probability, quantile, and random generation for normal, binomial, and more.

Normal distribution

print(pnorm(1.96))
print(qnorm(0.975))
set.seed(42)
print(rnorm(5))

Reproducible randomness

set.seed() fixes pseudo-random streams—critical for reproducible simulations and tests.

Important interview questions and answers

Q: What does pnorm give?
A: Cumulative probability P(X <= x) for the standard normal by default.
Q: Why set.seed?
A: Same seed yields identical random draws—needed for reproducible research.

Self-check

What prefix generates random draws?
What does qnorm(0.975) represent?

Tip: Always set.seed() before simulations you publish or regression-test.

Interview prep

rnorm vs rbinom?: rnorm continuous normal draws; rbinom discrete binomial trials.

Interview tip Lesson completion confidence

Can you explain this lesson in 30 seconds without reading notes?

Self-reflection (saved on this device)

Not saved yet.

Playground

Runs on the configured server runner (dev: npm run runner with LEARNING_RUNNER_ENABLED=true). Output appears below the editor.

Code runner not available

Server runner is disabled. Set LEARNING_RUNNER_ENABLED=true and LEARNING_RUNNER_URL in .env (see .env.example).

Check yourself

Multiple choice — immediate feedback.

Discussion

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Starter discussion topics

sample() vs runif?
set.seed why?

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