In order to set rates, an insurance company is trying to estimate the number of sick days that full-time workers at an auto repair shop take per year. A previous study indicated that the standard deviation was 2.8 days. How large a sample must be selected if the company wants to be 95% confident that the true mean differs from the sample mean by no more than 1 day?

Respuesta :

Answer: 31

Step-by-step explanation:

Formula to find the sample size is given by :_

[tex]n=(\dfrac{z^*\cdot \sigma}{E})^2[/tex]

, where z*= critical value corresponds to confidence level.

[tex]\sigma[/tex] = population standard deviation.

E= Margin of error.

As per given , we have

[tex]\sigma=2.8[/tex]

E=1

We know that critical value corresponding to 95% confidence level = z*=1.96

Then, the required sample size would be :

[tex]n=(\dfrac{(1.96)\cdot (2.8)}{1})^2[/tex]

[tex]n=(5.488)^2[/tex]

[tex]n=30.118144\approx31[/tex]

Hence, the required minimum sample size = 31

The sample size has to be 31 for it to be 95% confident and true mean differing from the sample mean by no more than 1 day.

What is Sample size?

This is the act of choosing the number of observations to be included in a statistical sample.

Sample size (n) =  (z* × б / E)²

where z*= critical value corresponds to confidence level , б = population standard deviation and E is margin of error.

= (1.96 × 2.8 /1 )²

= (5.488)²

= approximately 31.

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