Answer:
9.34%
Step-by-step explanation:
p = 4%, or 0.04
n = Sample size = 667
u = Expected value = n * p = 667 * 0.04 = 26.68
SD = Standard deviation = 
= 5.06
Now, the question is if the manager is correct, what is the probability that the proportion of flops in a sample of 667 released films would be greater than 5%?
This statement implies that the p-vlaue of Z when X = 5% * 667 = 33.35
Since,
Z = (X - u) / SD
We have;
Z = (33.35 - 26.68) / 5.06
Z = 1.32
From the Z-table, the p-value of 1.32 is 0.9066
1 - 0.9066 = 0.0934, or 9.34%
Therefore, the probability that the proportion of flops in a sample of 667 released films would be greater than 5% is 9.34%.
Answer:
it think it is D
Step-by-step explanation:
just take one of the number and move it for example 4x right and 2y up and then look at where the connection is.
2 X { 6 + [ 12 divided ( 3 + 1 ) ] } - 1
3 + 1 = 4
12 divided by 4 is 3
2 X { 6 + [ 3 ] } - 1
6 + 3 = 9
2 X { 9 } - 1
9 X 2 = 18
18 - 1 = 17!
17 is the answer
I used PEMDAS
P - Parenthesis
E - Exponents
M - Multiplication
D - Division
A - Addition
S - Subtraction
[in order that your supposed to do]
Answer:
6,561
Step-by-step explanation:
(-9)^4 = -9*-9*-9*-9= 6,561
Answer:
The price of the homes in the Pittsburgh sample typically vary by about $267,210 from the mean home price of $500,000.
Step-by-step explanation:
The dotplots reveal that the variability of home prices in the Pittsburgh sample is greater than the variability of home prices in the Philadelphia sample. Therefore, the standard deviation of the home prices for the Pittsburgh sample is $267,210 rather than $100,740. The correct interpretation of this statistic is that the price of homes in Pittsburgh typically vary by about $267,210 from the mean home price of $500,000.
