# 10/26/2022

## Continuous Random Variables

- Uniform distribution
- dunif(k, min, max), punif(k, min, max), and runif(n, min, max) with RStudio

- Normal distribution
- dnorm(k, mean, sd), pnorm(k, mean, sd), and rnorm(n, mean, sd) with RStudio
- some students prefer xpnorm and xqnorm with the mosaic package

- Student's t-distribution
- dt(k, df), pt(k, df), and rt(n, df) with RStudio

- Cauchy distribution
- dcauchy(k), pcauchy(k), and rcauchy(n) with RStudio

- Chi-squared distribution
- dchisq(k, df), pchisq(k, df), and rchisq(n, df) with RStudio

- Gamma distribution
- dgamma(k, shape, scale), pgamma(k, shape, scale), and rgamma(n, shape, scale) with RStudio

- F-distribution
- df(k, df1, df2), pf(k, df1, df2), and rf(n, df1, df2) with RStudio

- Exponential distribution
- dexp(k, rate), pexp(k, rate), and rexp(n, rate) with RStudio

- Beta distribution
- dbeta(k, shape1, shape2), pbeta(k, shape1, shape2), and rbeta(n, shape1, shape2) with RStudio

- Lots of other distributions - (e.g., check out the logistic, log normal, and Weibull distributions)

## Visualizing Distributions

- See DistributionPlots.R on our Google Drive folder for examples of both discrete and continuous distributions. In short, there are lots of ways to create these plots in R, so explore and have fun with these distributions.

## Reminder: Please send me an email message (before October 27) that includes a short description of your resampling and simulation plans for your second project, whether you will be working alone or with a partner, and the preferred date for your presentation (between October 31 and November 7).

## We will have a problem session on Friday.