Simulate Data from the Standard Normal Distribution

Run the chunk of code several times and look at the pattern in the Normal Q-Q Plot. Do you see linear trend?

randomdata=rnorm(100, 0, 1)
qqnorm(randomdata)
qqline(randomdata)

Simulate Uniform data on the interval from 0 to 1.

Run the chunk of code several times. Clearly describe the departures from linear trend that indicate a lack of normality.

randomdata2=runif(100, 0, 1)
qqnorm(randomdata2)
qqline(randomdata2)

Simulate data from a t distribution with 1 degree of freedom. This distribution is also known as the Cauchy distribution.

Run the chunk of code several times. Clearly describe the departures from linear trend that indicate a lack of normailty.

randomdata3=rt(100, 1)
qqnorm(randomdata3)
qqline(randomdata3)

Simulate data from a t distribution with 1 degree of freedom. This distribution is also known as the Cauchy distribution.

Run the chunk of code several times. Clearly describe the departures from linear trend that indicate a lack of normailty.

randomdata3=rt(100, 1)
qqnorm(randomdata3)
qqline(randomdata3)