A certain airline wishes to estimate the mean number of seats that are empty on flights that use 737-airplanes. There are 189 seats on a 737. To do so, the airline randomly picks n=36 flights. For each flight, the number of empty seats is counted. The data are given below. 41, 31, 34, 42, 35, 41, 35, 33, 50, 31, 36, 30, 37, 32, 38, 39, 27, 40, 30, 34, 31, 26, 29, 44, 31, 38, 36, 39, 31, 37, 38, 16, 37, 32, 43, 28 (a) Find the mean and the standard deviation of this sample. Use at least three decimal places in each answer. X= ________ empty seats S= __________empty seats (b) Find a 96% Student T confidence interval for μ, the mean number of empty seats on this airline's flights that use 737s. Use at least three decimal points for your lower and upper bounds. To avoid rounding errors you should use R-Stuido and not Tables. Lower Bound = ________ empty seats Upper Bound = __________ empty seats

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A certain airline wishes to estimate the mean number of seats that are empty on flights that use 737-airplanes. There are 189 seats on a 737. To do so, the airline randomly picks n=36 flights. For each flight, the number of empty seats is counted. The data are given below.

41, 31, 34, 42, 35, 41, 35, 33, 50, 31, 36, 30, 37, 32, 38, 39, 27, 40, 30, 34, 31, 26, 29, 44, 31, 38, 36, 39, 31, 37, 38, 16, 37, 32, 43, 28



(a) Find the mean and the standard deviation of this sample. Use at least three decimal places in each answer.

X= ________ empty seats

S= __________empty seats


(b) Find a 96% Student T confidence interval for μ, the mean number of empty seats on this airline's flights that use 737s. Use at least three decimal points for your lower and upper bounds. To avoid rounding errors you should use R-Stuido and not Tables.

Lower Bound = ________ empty seats

Upper Bound = __________ empty seats


(c) Find a 96% confidence interval for μ, the mean number of empty seats on this airline's flights that use 737s, by Bootstrapping 1000 samples. Use the seed 497 to ensure that R-Studio "randomly" samples the same "random" samples as this question will expect.

You can do this by including the code, you can copy it into your R-Studio to bootstrap your samples.

RNGkind(sample.kind="Rejection");
set.seed(497);
B=do(1000) * mean(resample(c(41, 31, 34, 42, 35, 41, 35, 33, 50, 31, 36, 30, 37, 32, 38, 39, 27, 40, 30, 34, 31, 26, 29, 44, 31, 38, 36, 39, 31, 37, 38, 16, 37, 32, 43, 28), 36));

Ignore any errors or warnings that show up.

Use at least three decimal points for your lower and upper bounds.

Lower Bound = __________ empty seats

Upper Bound = ________empty seats

 
 
 
 
 
 
Distribution of Empty Seats
10
2.
15
20
25
30
35
40
45
50
Number of Unoccupied Seats
12
8
9
4.
Frequency
Transcribed Image Text:Distribution of Empty Seats 10 2. 15 20 25 30 35 40 45 50 Number of Unoccupied Seats 12 8 9 4. Frequency
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