EBook Problems EDA IntroVar

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:''(d) Mean = 60, standard deviation = -8
:''(d) Mean = 60, standard deviation = -8
{{hidden|Answer|(b)}}
{{hidden|Answer|(b)}}
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===Problem 5===
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A physician collected data on 1000 patients to examine their heights. A statistician hired to look at the files noticed the typical height was about 60 inches, but found that one height was 720 inches. This is clearly an outlier. The physician is out of town and can't be contacted, but the statistician would like to have some preliminary descriptions of the data to present when the doctor returns. Which of the following best describes how the statistician should handle this outlier?
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*Choose one answer.
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:''(a) The statistician should publish a paper on the emergence of a new race of giants.
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:''(b) The statistician should keep the data point in; each point is too valuable to drop one.
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:''(c) The statistician should drop the observation from the analysis because this is clearly a mistake; the person would be 60 feet tall.
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:''(d) The statistician should analyze the data twice, once with and once without this data point, and then compare how the point affects conclusions.
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:''(e) The statistician should drop the observation from the dataset because we can't analyze the data with it.
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{{hidden|Answer|(c)}}
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* [[EBook | Back to Ebook]]
* [[EBook | Back to Ebook]]

Revision as of 18:58, 1 January 2009

Contents

EBook Problems Set - The Nature of Data and Variation Problems

Problem 1

Researchers do a study on the number of cars that a person owns. They think that the distribution of their data might be normal, even though the median is much smaller than the mean. They make a p-plot. What does it look like?

  • Choose one answer.
(a) It's not a straight line.
(b) It's a bell curve.
(c) It's a group of points clustered around the middle of the plot.
(d) It's a straight line.


Problem 2

Bicycles arrive at a bike shop in boxes. Before they can be sold, they must be unpacked, assembled, and tuned (lubricated, adjusted,etc). Based on past experience, the shop manager makes the following assumptions about how long this may take: The times for each setup phase are independent The times for each phase follow a Normal curve The means and standard deviations of the times (in minutes) are as shown

Phase Mean SD
Unpacking 3.5 0.7
Assembly 21.8 2.4
Tuning 21.8 2.7

What are the mean and standard deviation for the total bicycle set up time?

  • Choose one answer.
(a) Mean = 100 min, standard deviation = 12 min
(b) Can't be determined with the information given
(c) Mean = 37.6 min, standard deviation = 3.7 min
(d) Mean = 20 min, standard deviation = 13.69 min


Problem 3

Let X be a random variable with mean 80 and standard deviation 12. Find the mean and the variance of the following variable: 2X-100

  • Choose one answer.
(a) Mean = 100, variance = 288
(b) Mean = 60, variance = 12
(c) Mean = 160, variance = 144
(d) Mean = 60, variance = 576


Problem 4

Let X be a random variable with mean 80 and standard deviation 12. Find the mean and the standard deviation of the following variable: X- 20

  • Choose one answer.
(a) Mean = 60, standard deviation = 144
(b) Mean = 60, standard deviation = 12
(c) Mean = 80, standard deviation = 12
(d) Mean = 60, standard deviation = -8


Problem 5

A physician collected data on 1000 patients to examine their heights. A statistician hired to look at the files noticed the typical height was about 60 inches, but found that one height was 720 inches. This is clearly an outlier. The physician is out of town and can't be contacted, but the statistician would like to have some preliminary descriptions of the data to present when the doctor returns. Which of the following best describes how the statistician should handle this outlier?

  • Choose one answer.
(a) The statistician should publish a paper on the emergence of a new race of giants.
(b) The statistician should keep the data point in; each point is too valuable to drop one.
(c) The statistician should drop the observation from the analysis because this is clearly a mistake; the person would be 60 feet tall.
(d) The statistician should analyze the data twice, once with and once without this data point, and then compare how the point affects conclusions.
(e) The statistician should drop the observation from the dataset because we can't analyze the data with it.





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