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MAVERICK [17]
3 years ago
10

A company that produces white bread is concerned about the distribution of the amount of sodium in its bread. The company takes

a simple random sample of 100 slices of bread and computes the sample mean to be 103 milligrams of sodium per slice. Construct a 99% confidence interval for the unknown mean sodium level assuming that the population standard deviation is 10 milligrams.
Mathematics
1 answer:
Vesna [10]3 years ago
7 0

Answer:

The 99% confidence interval for the unknown mean sodium level is between 100.42 milligrams of sodium per slice and 105.58 milligrams of sodium per slice.

Step-by-step explanation:

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

\alpha = \frac{1 - 0.99}{2} = 0.005

Now, we have to find z in the Ztable as such z has a pvalue of 1 - \alpha.

That is z with a pvalue of 1 - 0.005 = 0.995, so Z = 2.58.

Now, find the margin of error M as such

M = z\frac{\sigma}{\sqrt{n}}

In which \sigma is the standard deviation of the population and n is the size of the sample.

M = 2.58\frac{10}{\sqrt{10}} = 2.58

The lower end of the interval is the sample mean subtracted by M. So it is 103 - 2.58 = 100.42 milligrams of sodium per slice.

The upper end of the interval is the sample mean added to M. So it is 103 + 2.58 = 105.58 milligrams of sodium per slice.

The 99% confidence interval for the unknown mean sodium level is between 100.42 milligrams of sodium per slice and 105.58 milligrams of sodium per slice.

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Answer:

182.167-2.03\frac{114.05}{\sqrt{36}}=143.580  

182.167+2.03\frac{114.05}{\sqrt{36}}=220.754  

So on this case the 95% confidence interval would be given by (143.580;220.754)  

Step-by-step explanation:

Assuming the following dataset:

77, 349,417,349, 167 , 225, 265, 360,205

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We can calculate the sample mean with the followinf formula:

\bar X = \frac{\sum_{i=1}^n X_i}{n}= 182.167

And the sample deviation with:

s = \sqrt{\frac{\sum_{i=1}^n (X_i-\bar X)^2}{n-1}}=114.05

The sample size on this case is n =36.

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=182.167 represent the sample mean  

\mu population mean (variable of interest)  

s=114.05 represent the sample standard deviation  

n=36 represent the sample size    

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

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

The point estimate of the population mean is \hat \mu = \bar X =182.167

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

df=n-1=36-1=35  

Since the Confidence is 0.95 or 95%, the value of \alpha=0.05 and \alpha/2 =0.025, and we can use excel, a calculator or a table to find the critical value. The excel command would be: "=-T.INV(0.025,35)".And we see that t_{\alpha/2}=2.03  

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

182.167-2.03\frac{114.05}{\sqrt{36}}=143.580  

182.167+2.03\frac{114.05}{\sqrt{36}}=220.754  

So on this case the 95% confidence interval would be given by (143.580;220.754)  

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