I think the answer is x2 + 3x -28 and the x2 is x to the POWER of 2
Using the normal distribution, there is a 0.2076 = 20.76% probability that the proportion of persons with a college degree will differ from the population proportion by greater than 3%.
<h3>Normal Probability Distribution</h3>
The z-score of a measure X of a normally distributed variable with mean
and standard deviation
is given by:

- The z-score measures how many standard deviations the measure is above or below the mean.
- Looking at the z-score table, the p-value associated with this z-score is found, which is the percentile of X.
- By the Central Limit Theorem, for a proportion p in a sample of size n, the sampling distribution of sample proportion is approximately normal with mean
and standard deviation
, as long as
and
.
The proportion estimate and the sample size are given as follows:
p = 0.45, n = 437.
Hence the mean and the standard error are:
The probability that the proportion of persons with a college degree will differ from the population proportion by greater than 3% is <u>2 multiplied by the p-value of Z when X = 0.45 - 0.03 = 0.42</u>.
Hence:

By the Central Limit Theorem:

Z = (0.42 - 0.45)/0.0238
Z = -1.26
Z = -1.26 has a p-value of 0.1038.
2 x 0.1038 = 0.2076.
0.2076 = 20.76% probability that the proportion of persons with a college degree will differ from the population proportion by greater than 3%.
More can be learned about the normal distribution at brainly.com/question/28159597
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"Perimeter" is the distance all the way around the drawing. If the drawing has sides, then the perimeter is the SUM of the lengths of all the sides. It's exactly the distance an ant would have to walk along the line, to get all the way around to where he started from.
To get the perimeter of the triangle, you have to add up the lengths of the three sides.
(2a - 3) + (2a) + (3a + 1) =
2a - 3 + 2a + 3a + 1 .
Add up all the 'a's: 2a + 2a + 3a = 7a
Add up all the just plain numbers: -3 + 1 = -2
Write them together, as a binomial: 7a - 2
THAT's your expression for the perimeter.