When testing gas pumps for accuracy, fuel-quality enforcement specialists tested pumps andfound that 1304 of them were not pumpi
1 answer:
Answer:
The p-value of the test statistic from the standard normal table is 0.0017 which is less than the level of significance therefore, the null hypothesis would be rejected and it can be concluded that there is sufficient evidence to support the claim that less than 20% of the pumps are inaccurate.
Step-by-step explanation:
Here, 1304 gas pumps were not pumping accurately and 5689 pumps were accurate.
x = 1304, n = 1304 + 5689 = 6993
The level of significance = 0.01
The sample proportion of pump which is not pumping accurately can be calculated as,
The claim is that the industry representative less than 20% of the pumps are inaccurate.
The hypothesis can be constructed as:
H0: p = 0.20
H1: p < 0.20
The one-sample proportion Z test will be used.
The test statistic value can be obtained as:
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Answer:
Using the critical value method we need to find a critical value in the t distribution who accumulates 0.025 of the area on the right and we got:
So then since our calculated value is lower then the critical value we fail to reject the null hypothesis and we can't conclude that the true mean resting pulse rate of people who do not exercise regularly is larger than the mean resting pulse rate of people who exercise regularly.
Step-by-step explanation:
Information given
represent the mean for sample of people who do not exercise
represent the mean for sample of people who do exercise
represent the sample standard deviation for 1
represent the sample standard deviation for 2
sample size for the group 1
sample size for the group 2
Significance level
t would represent the statistic
System of hypothesis
We want to verify if the mean resting pulse rate of people who do not exercise regularly is larger than the mean resting pulse rate of people who exercise regularly, the system of hypothesis would be:
Null hypothesis:
Alternative hypothesis:
The statistic for this case would be given by:
(1)
The degrees of freedom are given by:
Replacing the info given we got:
Using the critical value method we need to find a critical value in the t distribution who accumulates 0.025 of the area on the right and we got:
So then since our calculated value is lower then the critical value we fail to reject the null hypothesis and we can't conclude that the true mean resting pulse rate of people who do not exercise regularly is larger than the mean resting pulse rate of people who exercise regularly.
The area equation here is:
That means that the area depends on the width measurement of the rectangle.
To graph a quadratic function you have to see if the parabole is positive and the transformations, in this case, are positive and have a multiplication by two, which means that the graphics in x=1 and x=-1 will be y=2
Finally, you can conclude that there, you have a relationship between the area and the width of the rectangle because is a quadratic relationship and the area will increase in a quadratic form according to the increase of the width.
