Answer:
The probability that the sample proportion will differ from the population proportion by greater than 0.03 is 0.009.
Step-by-step explanation:
According to the Central limit theorem, if from an unknown population large samples of sizes n > 30, are selected and the sample proportion for each sample is computed then the sampling distribution of sample proportion follows a Normal distribution.
The mean of this sampling distribution of sample proportion is:

The standard deviation of this sampling distribution of sample proportion is:

As the sample size is large, i.e. <em>n</em> = 492 > 30, the central limit theorem can be used to approximate the sampling distribution of sample proportion by the normal distribution.
The mean and standard deviation of the sampling distribution of sample proportion are:

Compute the probability that the sample proportion will differ from the population proportion by greater than 0.03 as follows:

![=P(|Z|>2.61)\\\\=1-P(|Z|\leq 2.61)\\\\=1-P(-2.61\leq Z\leq 2.61)\\\\=1-[P(Z\leq 2.61)-P(Z\leq -2.61)]\\\\=1-0.9955+0.0045\\\\=0.0090](https://tex.z-dn.net/?f=%3DP%28%7CZ%7C%3E2.61%29%5C%5C%5C%5C%3D1-P%28%7CZ%7C%5Cleq%202.61%29%5C%5C%5C%5C%3D1-P%28-2.61%5Cleq%20Z%5Cleq%202.61%29%5C%5C%5C%5C%3D1-%5BP%28Z%5Cleq%202.61%29-P%28Z%5Cleq%20-2.61%29%5D%5C%5C%5C%5C%3D1-0.9955%2B0.0045%5C%5C%5C%5C%3D0.0090)
Thus, the probability that the sample proportion will differ from the population proportion by greater than 0.03 is 0.009.
28 in^2
Divide shape into one rectangle and two squares:
Area of rectangle:
10 x 2 = 20 in^2
Area of one square:
2 x 2 = 4 in^2
Multiply that by 2 because we have 2 squares similar in size:
4 in^2 x 2 = 8 in^2
Add the area of the rectangle and two squares:
20 in^2 + 8 in^2 = 28 in^2
Have a nice day
Hope this helps!
Positive and negative doesn’t matter. Steepest slope is the smallest or largest number.
In this case D. -4
Hey I tried, hope it helps... can't work it out, all the best
Answer:
0.0049
Step-by-step explanation: