Download R`s Normal Distribution Alphabet

R's Normal Distribution Alphabet
Where we're headed
• In the last lab, you were able to overlay a
normal curve on histograms of data to help
you decide if the data's distribution is close to
a normal distribution.
• In this lab, we'll learn how to use some other
R functions to calculate percentages of normal
distributions.
Using the normal model
The distribution of female heights is Normally distributed with a
mean of 64.2 inches and standard deviation of 2.9 inches.
In order to find my percentile in this distribution, I had to
calculate my z-score and use the table for the standard Normal
curve.
To have Rstudio calculate percentiles, use the following code:
pnorm(____, mean = , sd = ____)
Calculate my percentile. My height is 67 inches.
P's and Q's
• We've seen that we can use pnorm to
calculate percentiles based on a specified
quantity. Hence, why we call it “P” norm.
• Now we'll see how to do the opposite. That is,
calculate a quantity for a specific percentile.
Hence why we'll call this a “Q” norm.
Q’s
Use the code:
qnorm(____, mean = ____, sd = ____)
to find the height of a female who is taller than
30% of all females?
Ketchup
• A fast food restaurant has just installed a new
automatic ketchup dispenser for use in
preparing its burgers. The amount of ketchup
dispensed by the machine follows a Normal
distribution with mean 1.05 ounces and
standard deviation 0.08 ounces.
Putting it all together
• Create a Normal density curve that models
this data.
• At what percentile is a quantity of 1 ounce of
ketchup?
• How much ketchup was dispensed if it was at
the 20th percentile in the distribution?
• If the restaurant’s goal is to put between 1
and 1.2 ounces of ketchup on each burger,
what percent of the time will this happen?