Show transcribed image text Consider the normal distribution N(μ (a) Find the lower quartile Q1. 50.97 57, σ = 9). (b) Find the upper quartile Qs. 63.03 (c) Find the interquartile range (IQR). 12.06 (d) Find the area to the left of Q1 -1.5 IQR. 0.0037 (e) Find the area to the right of Qs+1.5 IQR (f) Suppose you have a data set with 1000 values that can be approximated by the normal distribution with μ-36.7 and σ How many values do you expect to be outside of the interval (Q1 -1.5 IQR, Qs +1.5.IQR)?X (g) Generate 1000 random values of the normal distribution N(μ-57,o ) and store them in the variable z as follows: set seed(2202) x-rnorm(1000, mean=57, sd:9) Now create a boxplot and count the number of outliers. How many did you count? x 0.4.
Consider the normal distribution N(μ (a) Find the lower quartile Q1. 50.97 57, σ = 9). (b) Find the upper quartile Qs. 63.03 (c) Find the interquartile range (IQR). 12.06 (d) Find the area to the left of Q1 -1.5 IQR. 0.0037 (e) Find the area to the right of Qs+1.5 IQR (f) Suppose you have a data set with 1000 values that can be approximated by the normal distribution with μ-36.7 and σ How many values do you expect to be outside of the interval (Q1 -1.5 IQR, Qs +1.5.IQR)?X (g) Generate 1000 random values of the normal distribution N(μ-57,o ) and store them in the variable z as follows: set seed(2202) x-rnorm(1000, mean=57, sd:9) Now create a boxplot and count the number of outliers. How many did you count? x 0.4.
