Answer:
The 90% confidence interval would be given by (57.006;62.994)
Step-by-step explanation:
Previous concepts
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".
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".
[tex]\bar X=60[/tex] represent the sample mean
[tex]\mu[/tex] population mean (variable of interest)
[tex]\sigma=10[/tex] represent the population standard deviation
n=30 represent the sample size
Assuming the X follows a normal distribution
[tex]X \sim N(\mu, \sigma=10)[/tex]
The sample mean [tex]\bar X[/tex] is distributed on this way:
[tex]\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})[/tex]
The confidence interval on this case is given by:
[tex]\bar X \pm z_{\alpha/2}\frac{\sigma}{\sqrt{n}}[/tex] (1)
The next step would be find the value of [tex]\z_{\alpha/2}[/tex], [tex]\alpha=1-0.90=0.1[/tex],[tex]\alpha/2 =0.05[/tex] and [tex]z_\alpha/2=1.64[/tex]
Using the normal standard table, excel or a calculator we see that:
[tex]z_{\alpha/2}=1.64[/tex]
Since we have all the values we can replace:
[tex]60 - 1.64\frac{10}{\sqrt{30}}=57.006[/tex]
[tex]60 + 1.64\frac{10}{\sqrt{30}}=62.994[/tex]
So on this case the 90% confidence interval would be given by (57.006;62.994)