# 8/29/2022

## Comments on your Reading Assignment

• Data science versus statistics
• Case Study - sabermetrics (Bill James)
• Money Ball (Billy Bean)
• Buffalo Bills (Dennis Lock)
• Charlotte Hornets (Alexander Powell)
• tidyverse and piping
• Questions?

## Loading packages

• mosaic and mosaicData - lots of useful tools and resources
• mdsr - resources for our textbook
• fed16 (fed, fed12, etc.) - Federal Elections Commission
• macleish - field station weather data
• IMDbPY - Python package for internet movie database
• LOTS of others (later)

## Question for the class

• For those of you with R and RStudio experience, what is one tip for new users of RStudio? That is, what is one thing that you wish you would have been told when you started using R and RStudio?

## Class Activity - Our first set of simulations

• Generate 100 uniform(0, 1) random numbers using runif().
• Summarize the distribution with a histogram. Does the shape of the distribution match what you expected?
• Comment on the center, shape, and spread.
• Use qqnorm() and qqline() to check normality.
• Use t.test to check if the random number generator matches the expected mean.
• Create a new variable y = 2x that doubles the range of simulated values
• Create a new variable that generates uniform random numbers between -3 and 3.
• Generate 100 normal(0, 1) random numbers using rnorm().
• Summarize the distribution with a histogram. Does the shape of the distribution match what you expected?
• Comment on the center, shape, and spread.
• Use qqnorm() and qqline() to check normality.
• Change the mean and standard deviation to other values of your choice. Does the shape of the quantile plot change as you change the mean and standard deviation?
• Generate 100 binomial(31, .5) random numbers using rbinom().
• Summarize the distribution with a histogram.
• Comment on the center, shape, and spread.
• Use qqnorm() and qqline() to check normality. Is the distribution approximately normal?
• Change the number of trials and the probability of success to other values of your choice. Does the shape of the distribution change as you change the values of n and p? Make sure that you try some values of p close to zero and others close to 1.
• Generate 100 geometric(1/6) random numbers using rgeom().
• Summarize the distribution with a histogram.
• Comment on the center, shape, and spread
• Use qqnorm() and qqline() to check normality. Is the distribution approximately normal?