A large on-demand, video streaming company is designing a large-scale survey to determine the mean amount of time corporate executives watch on-demand television. A small pilot survey of 10 executives indicated that the mean time per week is 12 hours, with a standard deviation of 3 hours. The estimate of the mean viewing time should be within 0.25 hour. The 95% level of confidence is to be used. How many executives should be surveyed? (Use z Distribution Table.)
How many executives should be surveyed? (Round the final answer to the next whole number.)

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Answer:

554 executives should be surveyed.

Step-by-step explanation:

We have that to find our [tex]\alpha[/tex] level, that is the subtraction of 1 by the confidence interval divided by 2. So:

[tex]\alpha = \frac{1 - 0.95}{2} = 0.025[/tex]

Now, we have to find z in the Z-table as such z has a p-value of [tex]1 - \alpha[/tex].

That is z with a pvalue of [tex]1 - 0.025 = 0.975[/tex], so Z = 1.96.

Now, find the margin of error M as such

[tex]M = z\frac{\sigma}{\sqrt{n}}[/tex]

In which [tex]\sigma[/tex] is the standard deviation of the population and n is the size of the sample.

Standard deviation of 3 hours.

This means that [tex]\sigma = 3[/tex]

The 95% level of confidence is to be used. How many executives should be surveyed?

n executives should be surveyed, and n is found with [tex]M = 0.25[/tex]. So

[tex]M = z\frac{\sigma}{\sqrt{n}}[/tex]

[tex]0.25 = 1.96\frac{3}{\sqrt{n}}[/tex]

[tex]0.25\sqrt{n} = 1.96*3[/tex]

[tex]\sqrt{n} = \frac{1.96*3}{0.25}[/tex]

[tex](\sqrt{n})^2 = (\frac{1.96*3}{0.25})^2[/tex]

[tex]n = 553.2[/tex]

Rounding up:

554 executives should be surveyed.