In a manufacturing process, a random sample of 9 manufactured bolts has a mean length of 3 inches with a variance of .09. What is the 90 percent confidence interval for the true mean length of the manufactured bolt?

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Answer:

[tex]3-1.86\frac{0.3}{\sqrt{9}}=2.81[/tex]    

[tex]3+ 1.86\frac{0.3}{\sqrt{9}}=3.19[/tex]    

So on this case the 90% confidence interval would be given by (2.81;3.19)  

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".

[tex]\bar X=3[/tex] represent the sample mean

[tex]\mu[/tex] population mean (variable of interest)

[tex]s= \sqrt{0.09}= 0.3[/tex] represent the sample standard deviation

n=9 represent the sample size  

Solution to the problem

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

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

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

[tex]df=n-1=9-1=8[/tex]

Since the Confidence is 0.90 or 90%, the value of [tex]\alpha=0.1[/tex] and [tex]\alpha/2 =0.05[/tex], and we can use excel, a calculator or a table to find the critical value. The excel command would be: "=-T.INV(0.05,8)".And we see that [tex]t_{\alpha/2}=1.86[/tex]

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

[tex]3-1.86\frac{0.3}{\sqrt{9}}=2.81[/tex]    

[tex]3+ 1.86\frac{0.3}{\sqrt{9}}=3.19[/tex]    

So on this case the 90% confidence interval would be given by (2.81;3.19)