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Amanda [17]
3 years ago
13

A laboratory tested 85 chicken eggs and found that the mean amount of cholesterol was 190 milligrams. Assume that the sample sta

ndard deviation is 11.7 milligrams. Construct a 95% confidence interval for the true mean cholesterol content, μ, of all such eggs. State your conclusion in a statistical sentence.
Mathematics
1 answer:
Serjik [45]3 years ago
5 0

Answer:   (182.356,\ 197.644)

Step-by-step explanation:

Given : Significance level : \alpha:1-0.95=0.05

Sample size : n=85

Critical value : z_{\alpha/2}=1.96

Sample mean : \overline{x}=190

Standard deviation : \sigma=11.7

The confidence interval for population mean is given by :-

\overline{x}\pm z_{\alpha/2}\dfrac{\sigma}{\sqrt{n}}\\\\=190\pm(1.96)\dfrac{11.7}{\sqrt{9}}\\\\=190\pm7.644\\\\=(190-7.644,\ 190+7.644)=(182.356,\ 197.644)

Thus, the 95% confidence interval for the true mean cholesterol content, μ, of all such eggs = (182.356,\ 197.644)

Hence, we conclude that the true population mean of amount of cholesterol lies between 182.356 and 197.644.

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Option A is wrong as both are on a straight line and in fact should add up to equal 180 and not be equal to each other

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z=\frac{0.64 -0.5}{\sqrt{\frac{0.5(1-0.5)}{75}}}=2.43  

Now we can calculate the p value with the following probability:

p_v =P(z>2.43)=0.0075 \approx 0.008  

Since the p value is lower than the significance level we have enough evidence to reject the null hypothesis and we can conclude that the true proportion for this case is higher than 0.5

Step-by-step explanation:

Data given and notation

n=75 represent the random sample taken

\hat p=0.64 estimated proportion of interest

p_o=0.5 is the value that we want to test

\alpha=0.05 represent the significance level

Confidence=95% or 0.95

z would represent the statistic

p_v represent the p value

System of hypothesis

We want to verify if the true proportion is higher than 0.5:  

Null hypothesis:p =0.5  

Alternative hypothesis:p > 0.5  

The statistic is given by:

z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}} (1)  

Replacing the info given we got:

z=\frac{0.64 -0.5}{\sqrt{\frac{0.5(1-0.5)}{75}}}=2.43  

Now we can calculate the p value with the following probability:

p_v =P(z>2.43)=0.0075 \approx 0.008  

Since the p value is lower than the significance level we have enough evidence to reject the null hypothesis and we can conclude that the true proportion for this case is higher than 0.5

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