SOLUTION: In preparing a report on the​ economy, we need to estimate the percentage of businesses that plan to hire additional employees in the next 60 days. ​a) How many randomly selec

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Question 1197972: In preparing a report on the​ economy, we need to estimate the percentage of businesses that plan to hire additional employees in the next 60 days.
​a) How many randomly selected employers must we contact in order to create an estimate in which we are 99​% confident with a margin of error of ​6%?
​b) Suppose we want to reduce the margin of error to 4​%. What sample size will​ suffice?
​c) Why might it not be worth the effort to try to get an interval with a margin of error of 1​%?
a) A sample size of ? is needed.
Part 2
​b) A sample size of ? is needed.


Answer by math_tutor2020(3817)   (Show Source): You can put this solution on YOUR website!

Part (a)

At 99% confidence, the z critical value is roughly z = 2.576
Use a table like this
https://www.sjsu.edu/faculty/gerstman/StatPrimer/t-table.pdf
to get that value. Look at the bottom row labeled "Z" and above the 99% confidence level.

You can also use a stats calculator or spreadsheet to determine this z critical value.

The desired margin of error is 6%, which means we want E = 0.06 or smaller.

We're not told the value of phat, which is the sample proportion of businesses that plan to hire additional employees in the next 60 days.

Use phat = 0.5 as a conservative estimate. This is the default value of phat if none is stated.

n = min sample size
n = phat*(1-phat)*(z/E)^2
n = 0.5*(1-0.5)*(2.576/0.06)^2
n = 460.817778 approximately
n = 461 always round UP to the nearest whole number

Here's why we round up to the nearest whole number.
Let's try n = 460 in the margin of error formula
E = z*sqrt(phat*(1-phat)/n)
E = 2.576*sqrt(0.5*(1-0.5)/460)
E = 0.060053
We're slightly over the 6% target.
Now try n = 461
E = z*sqrt(phat*(1-phat)/n)
E = 2.576*sqrt(0.5*(1-0.5)/461)
E = 0.059988
Now the error is either 6% or less, which meets the goal we're after.
This is why we round up to the nearest whole number for min sample size problems. This is to clear the hurdle needed.


Answer: 461 employers

===============================================================
Part (b)

Repeat the same set of steps as part (a), but this time we use E = 0.04
Keep everything else the same.

n = phat*(1-phat)*(z/E)^2
n = 0.5*(1-0.5)*(2.576/0.04)^2
n = 1036.84
n = 1037

Answer: 1037 employers

===============================================================
Part (c)

Now use E = 0.01

n = phat*(1-phat)*(z/E)^2
n = 0.5*(1-0.5)*(2.576/0.01)^2
n = 16589.44
n = 16590

We need to sample a lot more employers at this point (more than ten times as much compared to the result of part (b)), so it's more practical to go with the 6% or 4% margin of error instead.

Answer: Minimum sample size gets way too large

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