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MBA.Graduate Psychology,PHD in HRM
Strayer,Phoniex,
Feb-1999 - Mar-2006
MBA.Graduate Psychology,PHD in HRM
Strayer,Phoniex,University of California
Feb-1999 - Mar-2006
PR Manager
LSGH LLC
Apr-2003 - Apr-2007
After keeping track of his heating expenses for several​ winters, a homeowner believes he can estimate the monthly cost from the average daily Fahrenheit temperature using the model Cost=129−1.95 temp. The residuals plot for his data is shown.
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a) Interpret the slope of the line in this context. What does the model predict given a 1° increase in​ temperature?
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A.
The model predicts a ​$129 increase in heating cost.
B.
The model predicts a ​$1.95 increase in heating cost.
C.
The model predicts a ​$129 decrease in heating cost.
D.
The model predicts a ​$1.95 decrease in heating cost.
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​b) Interpret the​ y-intercept of the line in this context. What does the model predict given a temperature of 0°​?
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A.
The model predicts a heating cost of​ $0.
B.
The model predicts a heating cost of ​$1.95.
C.
The model predicts a heating cost of ​$129.
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​c) During the months when the temperature stays around freezing ​(32 degrees ° ​F), would you expect the cost predictions based on the model to be​ accurate, too​ low, or too​ high? Explain.
A.
Too low, because the residual is positive.
B.
Accurate, because the predicted and observed values are very close.
C.
Too high, because the residual is negative.
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d) What heating cost does the model predict for a month that averages 10°​?
cost=​$_______
​(Round to the nearest cent as​ needed.)
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​e) During one of the months on which the model is​ based, the temperature did average 10°. What were the actual heating costs for this​ month?
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The actual heating costs for this month were ​$_________
​(Round to the nearest dollar as​ needed.)
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f) Do you think the homeowner should use this​ model?
A.
No
B.
Yes
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Question 3)
A group of high school seniors took a scholastic aptitude test. The resulting math scores had a mean 480.4 with a standard deviation of 190.1​, verbal scores had a mean 480.6 with a standard deviation of 162.3​, and the correlation between verbal and math scores was r=0.718. Complete parts a through f below.
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a)What is the​ correlation?
The correlation is:_________
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c) In​ general, what would a negative residual mean in this​ context?
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A.   a negative residual means the student has
a higher verbal score than than the linear model would predict.
B.
A negative residual means the student has
the exact verbal score that the linear model would predict.
C.
A negative residual means the student has a lower verbal score than the linear model would predict.
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​d) A person tells you her math score was 241. Predict her verbal score.
The student is expected to have a verbal score of ___.
​(Round to three decimal places as​ needed.)
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​e) Using the predicted verbal score from part​ (d) and the regression equation Math=76.215 +0.841(verbal)​, predict the​ student's math score.
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The predicted math score is:______.
​(Round to three decimal places as​ needed.)
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​f) Why​ doesn't the result in part​ (e) come out to 241​?
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A.
The line given in part​ (e) minimizes squared residuals in the verbal​ direction, while the line found in part​ (b) minimizes them in the math direction.
B.
The line found in part​ (b) minimizes squared residuals in the math​ direction, while the line given in part​ (e) minimizes them in the verbal direction.
C.
The line found in part​ (b) minimizes squared residuals in the verbal​ direction, while the line given in part​ (e) minimizes them in the math direction.
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question 4)
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The scatterplot to the right shows that the trend for the interest rate on a​ 3-month bond changed dramatically after​ 1980, so two regression models were fit to the relationship between the rate​ (in %) and the number of years since​ 1950, one for 1950 to 1980 and one for the data from 1980 to 2007. The accompanying display shows the plots of the interest rate on the​ 3-month bond from 1950 to 1980 and from 1980 to 2007 and their corresponding regression models. Complete parts a through d.
​a) How does the model for the data between 1980 and 2007 compare to the one for the data between 1950 and​ 1980?
A.
The model for the data between 1980 and 2007 fits the data much better than the other model.
B.
The models are approximately equal.
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C.
The two models both fit​ well, but they have very different slopes.
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​b) What does the model for the data between 1980 and 2007 estimate the interest rate to have been in 1995​? How does this compare to the predicted rate obtained from the model for the data between 1950 and​ 1980, which is approximately 12​%?
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The model estimates that the interest rate was:______ ​% in 1995.
​(Round to one decimal place as​ needed.)
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c) How does the predicted value from the model for the data between 1980 to 2007 compare to the predicted value from the model for the data between 1950 and​ 1980, which is approximately 12​%?
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A.
The model for the data between 1980 and 2007 predicts the interest rate in 1995 to be much higher than the other model predicts.
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B.
The model for the data between 1980 and 2007 predicts the interest rate in 1995 to be about the same as the other model predicts.
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C.
The model for the data between 1980 and 2007 predicts the interest rate in 1995 to be much lower than the other model predicts.
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​c) Do you trust this newer predicted​ value?
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A.
Yes. R2=64.3% is large enough for the extrapolation to be safe
B.
Not really. Extrapolating 45 years beyond the beginning of these data would be dangerous and unlikely to be accurate.
C.
​Yes, because the​ x-value is within the range of the original data.
D.
Not really. Interest rates are too random to predict for any time.
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​d) Given these two​ models, what would you predict the interest rate on the​ 3-month bond will be in 2020​?
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A.
It would be best to take the mean of the predicted values from each​ model, which is about 8​%.
B.
It would be best to use the predicted value from the model for the data between 1980 and​ 2007, which is about 2​%.
C.
It would be best to use the predicted value from the model for the data between 1950 and​ 1980, which is about 18​%.
D.
It would be best not to predict the value because extrapolating beyond the​ x-values that were used to fit the model can be dangerous.
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Question 5)
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The accompanying table shows the height of the initial drop​ (in feet) and the duration of the ride​ (in seconds) of the 10 best roller coasters in a certain country. What do these data indicate about the height of the initial drop of a roller coaster and the duration of the​ ride, using correlation and a​ scatterplot?
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Construct a scatterplot of the data. Choose the correct answer below. which is the correct scatter plot?
B) Calculate the correlation coefficient.
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r=______
​(Round to three decimal places as​ needed.)
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c) What do these data indicate about the height of the initial drop of a roller coaster and the duration of the​ ride?
A.
​Generally, rides on coasters with a greater initial drop tend to last
somewhat shorter​, because the correlation indicates a weak association.
B.
​Generally, rides on coasters with a greater initial drop tend to last
somewhat longer​, because the correlation indicates a moderate association.
C.
​Generally, rides on coasters with a greater initial drop tend to last
longer, because the correlation indicates a strong association.
D.
​Generally, rides on coasters with a greater initial drop tend to last somewhat longer​, because the correlation indicates a weak association.
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