Answer:
> a<-rnorm(20,50,6)
> a
[1] 51.72213 53.09989 59.89221 32.44023 47.59386 33.59892 47.26718 55.61510 47.95505 48.19296 54.46905
[12] 45.78072 57.30045 57.91624 50.83297 52.61790 62.07713 53.75661 49.34651 53.01501
Then we can find the mean and the standard deviation with the following formulas:
> mean(a)
[1] 50.72451
> sqrt(var(a))
[1] 7.470221
Step-by-step explanation:
For this case first we need to create the sample of size 20 for the following distribution:

And we can use the following code: rnorm(20,50,6) and we got this output:
> a<-rnorm(20,50,6)
> a
[1] 51.72213 53.09989 59.89221 32.44023 47.59386 33.59892 47.26718 55.61510 47.95505 48.19296 54.46905
[12] 45.78072 57.30045 57.91624 50.83297 52.61790 62.07713 53.75661 49.34651 53.01501
Then we can find the mean and the standard deviation with the following formulas:
> mean(a)
[1] 50.72451
> sqrt(var(a))
[1] 7.470221
Answer:
Step-by-step explanation:
Answer:
x = 8
Step-by-step explanation:
Answer:
76
Step-by-step explanation:
There are 6 faces to the prism:
2 each of (Length x Width): 2(4 x 4) = 2(16) = 32 m²
2 each of (Length x Heighth): 2(4 x 8) = 2(32) = 64 m²
2 each of (Width x Heighth): 2(4 x 8) = 2(32) = 64 m²
The sum of the faces is the Surface Area (S.A.)
32 m² + 64 m² + 64 m² = S.A.
160 m² = S.A.