While visiting a memorial, a person approximated the angle of elevation to the top of the memorial to be 35º. After walking 255
ft closer, he guessed that the angle of elevation had increased by 17º. Approximate the height of the memorial, to the top of the memorial.
1 answer:
Draw a diagram to illustrate the problem as shown in the figure below.
Let h the height of the hill. =
At position A, the angle of elevation is 40°, and the horizontal distance to the foot of the hill is x.
By definition,
tan(40°) = h/x h = x tan40 = 0.8391x
(1)
At position B, Joe is (x - 450) ft from the foot of the hill. His angle of elevation is
40 + 18 = 58°.
By definition, tan(58°) = h/(x - 450)
h = (x - 450) tan(58°) = 1.6003(x-450)
h = 1.6003x - 720.135 (2)
Equate (1) and (2).
1.6003x - 720.135 = 0.8391x 0.7612x = 720.135
x = 946.0523
From (1), obtain
h = 0.8391*946.0523 = 793.8 ft
Answer: The height of the hill is approximately 794 ft (nearest integer)
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Answer:
a) Null hypothesis:
Alternative hypothesis:
b)
For this case the p value is given
If we compare the p value and the significance level given we see that
so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the true mean is higher than 15 at 5% of signficance.
c) Type I error, also known as a “false positive” is the error of rejecting a null hypothesis when it is actually true. Can be interpreted as the error of no reject an alternative hypothesis when the results can be attributed not to the reality.
So for this case a type I of error would be reject the hypothesis that the true mean is less or equal than 15 and is actually true.
Step-by-step explanation:
Data given and notation
represent the sample mean
represent the sample standard deviation
sample size
represent the value that we want to test
represent the significance level for the hypothesis test.
t would represent the statistic (variable of interest)
represent the p value for the test (variable of interest)
Part a: State the null and alternative hypotheses.
We need to conduct a hypothesis in order to check if the true mean for vacation days is higher than 15, the system of hypothesis would be:
Null hypothesis:
Alternative hypothesis:
If we analyze the size for the sample is < 30 and we don't know the population deviation so is better apply a t test to compare the actual mean to the reference value, and the statistic is given by:
(1)
t-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".
Part b: P-value and conclusion
The first step is calculate the degrees of freedom, on this case:
For this case the p value is given
Conclusion
If we compare the p value and the significance level given we see that
so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the true mean is higher than 15 at 5% of signficance.
Part c
Type I error, also known as a “false positive” is the error of rejecting a null hypothesis when it is actually true. Can be interpreted as the error of no reject an alternative hypothesis when the results can be attributed not to the reality.
So for this case a type I of error would be reject the hypothesis that the true mean is less or equal than 15 and is actually true.