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Arturiano [62]
3 years ago
13

A random sample of 12 recent college graduates reported an average starting salary of $54,000 with a standard deviation of $6,00

0.
a. Construct a 95% confidence interval for the mean starting salary of college graduates.

a. 50188 to 57812$
b. 45,0000 to 50,000$
c. 48,000 to 60,000$
d. 50,000 to 54000$

b. The National Association of Colleges and Employers reports that the mean starting salary for 2017 college graduates is $50,516. Does your confidence interval (part a) indicate that starting salaries have significantly changed since 2017? Why or why not?
Mathematics
1 answer:
Marianna [84]3 years ago
4 0

Answer: a.) $50188 to $57812

Step-by-step explanation: <u>Confidence</u> <u>Interval</u> (CI) is an interval of values in which we are confident the true mean is in.

The interval is calculated as

x ± z\frac{s}{\sqrt{n} }

a. For a 95% CI, z-value is 1.96.

Solving:

54,000 ± 1.96.\frac{6000}{\sqrt{12} }

54,000 ± 1.96\frac{6000}{3.464}

54,000 ± 1.96*1732.102

54,000 ± 3395

This means the interval is

50605 < μ < 57395

<u>With a 95% confidence interval, the mean starting salary of college graduates is between 50605 and 57395 or </u><u>from 50188 to 57812$.</u>

<u />

b. The mean starting salary for college students in 2017 is $50,516, which is in the confidence interval. Therefore, since we 95% sure the real mean is between 50188 and 57812, there was no significant change since 2017.

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The monthly cost of driving a car depends on the number of miles driven. Lynn found that in May it cost her $420 to drive 500 mi
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Step-by-step explanation:

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Answer:

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So the answer for this case would be n=5 rounded up to the nearest integer

Step-by-step explanation:

Previous concepts

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".

The margin of error is the range of values below and above the sample statistic in a confidence interval.

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

\bar X=22 represent the sample mean

\mu population mean (variable of interest)

s=2.5 represent the sample standard deviation

n represent the sample size  

ME = 2 represent the margin of error accepted

Solution to the problem

The confidence interval for the mean is given by the following formula:

\bar X \pm t_{\alpha/2}\frac{s}{\sqrt{n}}   (1)

The margin of error is given by this formula:

ME=z_{\alpha/2}\frac{\sigma}{\sqrt{n}}    (2)

And on this case we have that ME =2 and we are interested in order to find the value of n, if we solve n from equation (2) we got:

n=(\frac{z_{\alpha/2} s}{ME})^2   (3)

We can use as estimator for the population deviation the sample deviation \hat \sigma = s

The critical value for 90% of confidence interval now can be founded using the normal distribution. And in excel we can use this formla to find it:"=-NORM.INV(0.05;0;1)", and we got z_{\alpha/2}=1.640, replacing into formula (3) we got:

n=(\frac{1.640(2.5)}{2})^2 =4.2 \approx 5

So the answer for this case would be n=5 rounded up to the nearest integer

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