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Fofino [41]
2 years ago
15

An automobile manufacturer claims that its van has a 29.1 miles/gallon (MPG) rating. An independent testing firm has been contra

cted to test the MPG for this van since it is believed that the van has an incorrect manufacturer's MPG rating. After testing 200 vans, they found a mean MPG of 28.8. Assume the standard deviation is known to be 2.4. A level of significance of 0.01 will be used. State the hypotheses. Enter the hypotheses:
Mathematics
1 answer:
tangare [24]2 years ago
6 0

Answer:

z=\frac{28.8-29.1}{\frac{2.4}{\sqrt{200}}}=-1.768    

The p value would be given by this probability:

p_v =2* P(z 

Since the p value is higher than the significance level we have enough evidence to FAIL to reject the null hypothesis and then we can conclude that the true mean is not significantly different from 29.1 MPG

Step-by-step explanation:

Information given

\bar X=28.8 represent the sample mean

\sigma=2.4 represent the population standard deviation

n=200 sample size  

\mu_o =29.1 represent the value to verify

\alpha=0.01 represent the significance level

t would represent the statistic  

p_v represent the p value

Hypothesis to test

We want to verify if the true mean is equal to 29.1 MPG, the system of hypothesis would be:  

Null hypothesis:\mu = 29.1  

Alternative hypothesis:\mu \neq 29.1  

The statistic is given by:

z=\frac{\bar X-\mu_o}{\frac{\sigma}{\sqrt{n}}}  (1)  

Replacing the info:

z=\frac{28.8-29.1}{\frac{2.4}{\sqrt{200}}}=-1.768    

The p value would be given by this probability:

p_v =2* P(z

Since the p value is higher than the significance level we have enough evidence to FAIL to reject the null hypothesis and then we can conclude that the true mean is not significantly different from 29.1 MPG

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What's the sum of 2⁄5 and 2⁄4?
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2/5 + 2/4

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Answer:

(0.582-0.485) - 1.64 \sqrt{\frac{0.582(1-0.582)}{144796} +\frac{0.485(1-0.485)}{211693}}=0.0942  

(0.582-0.485) + 1.64 \sqrt{\frac{0.582(1-0.582)}{144796} +\frac{0.485(1-0.485)}{211693}}=0.09978  

And the 90% confidence interval would be given (0.0942;0.09978).  

We are confident at 90% that the difference between the two proportions is between 0.0942 \leq p_A -p_B \leq 0.09978

Step-by-step 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".  

p_A represent the real population proportion female for Biology

\hat p_A =\frac{84199}{144796}=0.582 represent the estimated proportion female for biology

n_A=144796 is the sample size for A

p_B represent the real population proportion female for calculus AB

\hat p_B =\frac{102598}{211693}=0.485 represent the estimated proportion female for Calculus AB

n_B=211693 is the sample size required for B

z represent the critical value for the margin of error  

The population proportion have the following distribution  

p \sim N(p,\sqrt{\frac{p(1-p)}{n}})  

The confidence interval for the difference of two proportions would be given by this formula  

(\hat p_A -\hat p_B) \pm z_{\alpha/2} \sqrt{\frac{\hat p_A(1-\hat p_A)}{n_A} +\frac{\hat p_B (1-\hat p_B)}{n_B}}  

For the 90% confidence interval the value of \alpha=1-0.90=0.1 and \alpha/2=0.05, with that value we can find the quantile required for the interval in the normal standard distribution.  

z_{\alpha/2}=1.64  

And replacing into the confidence interval formula we got:  

(0.582-0.485) - 1.64 \sqrt{\frac{0.582(1-0.582)}{144796} +\frac{0.485(1-0.485)}{211693}}=0.0942  

(0.582-0.485) + 1.64 \sqrt{\frac{0.582(1-0.582)}{144796} +\frac{0.485(1-0.485)}{211693}}=0.09978  

And the 90% confidence interval would be given (0.0942;0.09978).  

We are confident at 90% that the difference between the two proportions is between 0.0942 \leq p_A -p_B \leq 0.09978

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