Selling Price = -39.81 + 0.099*Size Size = -39.81 + 0.099*Selling Price Selling
ID: 3269055 • Letter: S
Question
Selling Price = -39.81 + 0.099*Size
Size = -39.81 + 0.099*Selling Price
Selling Price = 0.099 - 39.81*Size
Size = -0.099 - 39.81*Selling Price
2. Suppose the slope of the regression line is 1.055. Interpret this slope in context.
On average, if the size of a house increases by 1 square foot, we would expect the price of the house to increase by 1.055 thousands of dollars.
On average, if the size of a house increases by 1.055 square feet, we would expect the price of the house to increase by one thousand dollars.
If the size of a house increases by 1 square foot, we know the price of the house will increase by 1.055 thousands of dollars.
When the size of a house is 0 square feet, we would expect this house to sell for 1.055 thousands of dollars.
3. Suppose the y-intercept of the regression equation is -22.000. Interpret this y-intercept in context.
When the size of a house is -22.000 square feet, we would expect this house to sell for 0 thousands of dollars.
When the size of a house is 0 square feet, we would expect this house to sell for -22.000 thousands of dollars.
On average, as the size of house increases by 1 square foot, we would expect the price of the house to decrease by -22.000 thousands of dollars.
All houses that are 0 square feet will definitely sell for -22.000 thousands of dollars.
4. The following situation applies to Questions 4-5:
0.027
-25.732
0.885
0.822
5. What is the value of the correlation coefficient r?
0.9973
0.6755
0.8219
-0.8219
6. Which of the following makes NO distinction between an explanatory variable X and a response variable Y (i.e., you can interchange the roles of X and Y and get the same result)?
Correlation
Regression
Both correlation and regression make no distinction between X and Y.
7. If we know the value of b, the slope of the regression line, we can accurately guess the value for the correlation coefficient without looking at the scatterplot.
True
False
8. Researchers collected data on the number of breeding pairs of Scarlet Macaw in an isolated area of an Amazon rainforest in each of 8 years (X) and the percentage of males who returned the next year (Y). The data show that the percentage returning is lower after successful breeding seasons and that the relationship is roughly linear. The following shows a StatCrunch regression output for these data. What percentage of the variation in the percent of returning males can be explained by the number of breeding pairs?
Simple linear regression results:
Dependent Variable: percent.returned
Independent Variable: breeding.pairs
percent.returned = 136.682 - 3.218 breeding.pairs
Sample size: 8
R (correlation coefficient) = -0.8329
R-sq = 0.6937
Estimate of error standard deviation: 9.460
Parameter estimates:
Parameter
Estimate
Std. Err.
DF
T-Stat
P-Value
Intercept
136.682
22.684
6
5.696
0.0007
Slope
-3.218
0.613
6
-3.459
0.0106
-83%
-69%
69%
83%
9. The mean height of American women in their twenties is about 64 inches, and the standard deviation is about 2.7 inches. The mean height of men the same age is about 69.3 inches, with standard deviation about 2.8 inches. If the correlation between the heights of husbands and wives is about r = 0.5, what is the slope of the regression line used to predict the husband's height (Y) from the wife's height (X) in young couples?
Note: b = r(sy / sx)
1.0191
0.4821
0.5185
1.0370
10. For a biology project, you measure the weight, in grams, and the tail length, in millimeters (mm), of a group of mice. The equation of the least-squares line for predicting tail length from weight is
predicted tail length = 20 + 3*weight
Suppose a mouse weighing 20 grams has a 78 mm tail. What is the residual for this mouse?
-2 mm
80 mm
2 mm
0 mm
Parameter
Estimate
Std. Err.
DF
T-Stat
P-Value
Intercept
136.682
22.684
6
5.696
0.0007
Slope
-3.218
0.613
6
-3.459
0.0106
Explanation / Answer
Q1)Option A is Correct . Selling Price = -39.81 + 0.099*Size. because selling price should be on left side and slope should be positive
Q2)Option A is Correct. On average, if the size of a house increases by 1 square foot, we would expect the price of the house to increase by 1.055 thousands of dollars.
Q3) Option B is Correct.When the size of a house is 0 square feet, we would expect this house to sell for -22.000
thousands of dollars.
Q4) Option C is Correct. It is 0.885
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