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Answer:
The pvalue of the test is 0.017 > 0.01, which means that there is not convincing evidence that the mean time behind the whell for all U.S drivers is less than 51 minutes.
Step-by-step explanation:
U.S. drivers spend on average, 51 minutes behind the wheel each day.
This means that at the null hypothesis we test that:
[tex]H_{0}: \mu = 51[/tex]
Is there convincing evidence that the mean time behind the wheel for all U.S. drivers is less than 51 minutes?
This means that the alternate hypothesis is:
[tex]H_{a}: \mu < 51[/tex]
The test statistic is:
[tex]z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]
In which X is the sample mean, [tex]\mu[/tex] is the value tested at the null hypothesis, [tex]\sigma[/tex] is the standard deviation and n is the size of the sample.
51 is tested at the null hypothesis:
This means that [tex]\mu = 51[/tex]
The study revealed that the mean time behind the wheel for the sample of 75 drivers was 46.4 minutes with a standard deviation of 18.8 minutes.
This means that [tex]n = 75, X = 46.4, \sigma = 18.8[/tex]
Value of the test-statistic:
[tex]z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]
[tex]z = \frac{46.4 - 51}{\frac{18.8}{\sqrt{75}}}[/tex]
[tex]z = -2.12[/tex]
Pvalue of the test:
The pvalue of the test is the probability of finding a sample mean less than 46.4, which is the pvalue of z when X = 46.4.
Looking at the z-table, z = -2.12 has a pvalue of 0.017.
Decision:
The pvalue of the test is 0.017 > 0.01, which means that there is not convincing evidence that the mean time behind the whell for all U.S drivers is less than 51 minutes.
No, there isn't convincing evidence that the mean time behind the wheel for all U.S. drivers is less than 51 minutes.
Given the following data:
- Mean = 51.
- Number of drivers = 75 drivers.
- Sample mean (mean time) = 46.4 minutes.
- Standard deviation = 18.8 minutes.
What is a null hypothesis?
A null hypothesis ([tex]H_0[/tex]) can be defined the opposite of an alternate hypothesis ([tex]H_a[/tex]) and it asserts that two (2) possibilities are the same.
For the null hypothesis, we would test that:
[tex]H_o : \mu =51[/tex]
For the alternate hypothesis, we would test that:
[tex]H_a : \mu < 51[/tex]
The test statistics would be calculated with this formula:
[tex]Z=\frac{x\;-\;u}{\frac{\delta}{\sqrt{n} } }[/tex]
Where:
- x is the sample mean.
- u is the mean.
- [tex]\delta[/tex] is the standard deviation.
- n is the number of drivers.
Substituting the given parameters into the formula, we have;
[tex]Z=\frac{46.4\;-\;51}{\frac{18.8}{\sqrt{75} } }\\\\Z=\frac{-4.6}{\frac{18.8}{8.6603} }\\\\Z=\frac{-4.6}{2.1708 }[/tex]
Z = -2.12.
What is a p-value?
In Statistics, a p-value also known as the probability value is the probability which occurs when the null hypothesis ([tex]H_0[/tex]) is true of obtaining a sample mean that is at least as unlikely as what is observed by a researcher or scientist.
From the z-table, a z-score of -2.12 corresponds to or has a p-value of 0.017. Therefore, the p-value for this test is 0.017 > 0.01.
In conclusion, there isn't convincing evidence that the mean time behind the wheel for all U.S. drivers is less than 51 minutes.
Read more on null hypothesis here: https://brainly.com/question/14913351
