35. Which of the statements below describes the correlation for this problem?
a. As weight increases, price tends to also increase.
b. There is a strong positive linear relationship between weight and price.
c. You can use weight to predict price using a regression line and it would fit well.
d. All of the above.
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View Full Document36. The correlation would change if you changed the units of measurement to be grams for
weight and American dollars for price (True or False)
a. True
b. False
37.
Using information from the output above, what is the standard deviation of weight?
38. Interpret the slope found in the above output in terms of X and Y.
a. As X increases by 1, Y decreases by 259.63
b. As X increases by 1, Y increases by 3721.02
c. As X increases by 3,721.02, Y decreases by 259.63
d. None of the above.
Regression (Part 2)
Let x be the change in a stock market index in January and let y be the change in the
stock market index for the entire year. Descriptive statistics from 1960 to 1997 are
shown below.
Descriptive Statistics: Jan, Year
Total
Variable
Count
Mean
StDev
Minimum
Median
Maximum
Jan
37
0.018
0.016
0.002
0.020
0.200
Year
37
0.091
0.010
0.520
0.101
0.393
Pearson correlation of Jan and Year = 0.796
PValue = 0.895
39. Slope is in what units in the context of this problem?
*40. At which point on the best fitting line will you make the very best predictions? Give
an (x,y) point.
Data was collected on amount of rainfall (inches) and amount of corn produced
(bushels per acre) for a number of years in Kansas. The output is shown below.
Predictor
Coef
SE Coef
T
P
Constant
89.543
6.703
13.36
0.000
Rainfall
0.12800
0.01375
9.31
0.000
Correlation of Rainfall and Corn = 0.608
41. Find the value of r
2
for this problem.
42. Interpret the value of r
2
in this problem. (Make sure you can interpret the values of r2 in
each of the other problems in #138 above.)
*43. Suppose you know the value of r
2
. Can you just take its square root to get the correct
correlation? Explain why or why not. If not, what other info do you need to get the sign of
r?
44. An influential point always has a large residual (True or False)
45. A point with a large residual is an outlier in the vertical (Y) direction. (True or False)
46. A residual is the difference between what you predicted Y to be based on the line, and
what the actual of Y turned out to be in your data set. (True or False).
*47. Which of the following are affected by outliers?
a. The correlation
b. The slope of the regression line
c. The Yintercept of the regression line
d. All of the above
*48. The residual plot should show you a linear pattern if a regression line fits well. (True
or False)
*49. To fit a linear regression line all you need is a strong value of r. (True or False)
*50. The value of r
2
is always greater than or equal to the value of r.
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 Fall '11
 Johnson
 Statistics, Econometrics, Linear Regression, Regression Analysis, Descriptive statistics, Errors and residuals in statistics

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