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Semenov [28]
3 years ago
15

An automobile manufacturer claims that its van has a 40.3 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 250 vans, they found a mean MPG of 39.9. Assume the standard deviation is known to be 2.4. A level of significance of 0.05 will be used. Find the value of the test statistic. Round your answer to 2 decimal places.
Mathematics
1 answer:
vovikov84 [41]3 years ago
7 0

Answer:

The value of the test statistic is -2.64.

Step-by-step explanation:

The test statistic is:

t = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}

In which X is the sample mean, \mu is the expected(claimed) mean, \sigma is the standard deviation and n is the size of the sample.

An automobile manufacturer claims that its van has a 40.3 miles/gallon (MPG) rating.

This means that \mu = 40.3

After testing 250 vans, they found a mean MPG of 39.9. Assume the standard deviation is known to be 2.4.

This means, respectively, that:

n = 250, X = 39.9, \sigma = 2.4

So

t = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}

t = \frac{39.9 - 40.3}{\frac{2.4}{\sqrt{250}}}

t = -2.64

The value of the test statistic is -2.64.

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Margarita [4]

Answer:

t=\frac{107.75-116.75}{\sqrt{\frac{2.75^2}{4}+\frac{9.604^2}{4}}}}=-1.802  

The degrees of freedom are given by:

df=n_{1}+n_{2}-2=4+4-2=6

The p value for this case would be given by:

p_v =2*P(t_{(6)}

Since the p value is higher than the significance level we have enough evidence to FAIl to reject the null hypothesis and we can conclude that the true mean is not significantly different between the two types of battery

Step-by-step explanation:

Information given

Battery 1 106 111 109 105

Battery 2 125 103 121 118

We can calculate the mean and the deviation with the following formulas"

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

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

\bar X_{1}=107.75 represent the mean for the Battery 1

\bar X_{2}=116.75 represent the mean for the Bettery 2

s_{1}=2.75 represent the sample standard deviation for the Battery 1

s_{2}=9.604 represent the sample standard deviation for the battery 2

n_{1}=4 sample size selected for the Battery 1

n_{2}=4 sample size selected for the Battery 2

\alpha=0.1 represent the significance level

t would represent the statistic  

p_v represent the p value

System of hypothesis

We want to check if the difference in longevity between the two batteries, the system of hypothesis would be:

Null hypothesis:\mu_{1} = \mu_{2}

Alternative hypothesis:\mu_{1} \neq \mu_{2}

The statistic is given by:

t=\frac{\bar X_{s1}-\bar X_{2}}{\sqrt{\frac{s^2_{1}}{n_{1}}+\frac{s^2_{2}}{n_{2}}}} (1)

The statistic is given by:

t=\frac{107.75-116.75}{\sqrt{\frac{2.75^2}{4}+\frac{9.604^2}{4}}}}=-1.802  

The degrees of freedom are given by:

df=n_{1}+n_{2}-2=4+4-2=6

The p value for this case would be given by:

p_v =2*P(t_{(6)}

Since the p value is higher than the significance level we have enough evidence to FAIl to reject the null hypothesis and we can conclude that the true mean is not significantly different between the two types of battery

8 0
3 years ago
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