Question

A random sample of 110 lightning flashes in a certain region resulted in a sample average radar echo duration of 0.81 second and a sample standard deviation of 0.34 second. (a) Calculate a 99% confidence interval for the true average echo duration. (b) This sample data is used as a pilot study, and now the investigator would like to design a new study to construct a 99% confidence interval with width 0.1. What is the necessary sample size?

Answer 1

a)
`0.81-2.62(0.34)/(√(110))=0.725`

`0.81+2.62(0.34)/(√(110))=0.895`

So on this case the 99% confidence interval would be given by (0.725;0.895)

b)
`n=((2.58(0.34))/(0.1))^2 =76.95 \approx 77`

So the answer for this case would be n=77 rounded up to the nearest integer

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=0.81` represent the sample mean

`\mu` population mean (variable of interest)

s=0.34 represent the sample standard deviation

n=110 represent the sample size

Part a

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

`\bar X \pm t_(\alpha/2)(s)/(√(n))` (1)

In order to calculate the critical value
`t_(\alpha/2)` we need to find first the degrees of freedom, given by:

`df=n-1=110-1=109`

Since the Confidence is 0.99 or 99%, the value of
`\alpha=0.01` and
`\alpha/2 =0.005`, and we can use excel, a calculator or a table to find the critical value. The excel command would be: "=-T.INV(0.005,119)".And we see that
`t_(\alpha/2)=2.62`

Now we have everything in order to replace into formula (1):

`0.81-2.62(0.34)/(√(110))=0.725`

`0.81+2.62(0.34)/(√(110))=0.895`

So on this case the 99% confidence interval would be given by (0.725;0.895)

Part b

The margin of error is given by this formula:

`ME=z_(\alpha/2)(\sigmas)/(√(n))` (a)

And on this case we have that ME =0.1 and we are interested in order to find the value of n, if we solve n from equation (a) we got:

`n=((z_(\alpha/2) \sigma)/(ME))^2` (b)

We can assume the following estimator for the population deviation
`\hat \sigma =s =0.34`

The critical value for 99% of confidence interval now can be founded using the normal distribution. And in excel we can use this formla to find it:"=-NORM.INV(0.005;0;1)", and we got
`z_(\alpha/2)=2.58/tex], replacing into formula (b) we got: </p><p>[tex]n=((2.58(0.34))/(0.1))^2 =76.95 \approx 77`

So the answer for this case would be n=77 rounded up to the nearest integer