The data show the list and selling prices for several expensive homes. Find the regression equation, letting the the list price be the independent (x) va selling price of a home having a list price of $2 million. Is the result close to the actual selling price of $1.5 million? Use a significance level of 0.05. List price (millions of $) Selling price (millions of $) 3.4 3.6 3.4 3.7 2.8 2.4 2.1 2.1 2.6 2.8 2.6 1.6 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y =+x (Round to four decimal places as needed.) What is the best predicted selling price of a home having a list price of $2 million? The best predicted selling price for a home having a list price of $2 million is $million. (Round to two decimal place as needed.) Is the result close to the actual selling price of $1.5 million? O A. The result is close to the actual selling price of $1.5 million. O B. The result is exactly the same as the actual selling price of $1.5 million. O C. The result is not close to the actual selling price of $1.5 million.

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The data show the list and selling prices for several expensive homes. Find the regression equation, letting the the list price be the independent (x) variable. Find the best predicted
selling price of a home having a list price of $2 million. Is the result close to the actual selling price of $1.5 million? Use a significance level of 0.05.
List price (millions of $)
Selling price (millions of $)
2.8
3.4
3.4
2.1
2.4
2.6
2.6
3.6
3.7
1.6
2.1
2.8
Click the icon to view the critical values of the Pearson correlation coefficient r.
What is the regression equation?
y =+ x (Round to four decimal places as needed.)
What is the best predicted selling price of a home having a list price of $2 million?
The best predicted selling price for a home having a list price of $2 million is $
(Round to two decimal place as needed.)
million.
Is the result close to the actual selling price of $1.5 million?
O A. The result is close to the actual selling price of $1.5 million.
O B. The result is exactly the same as the actual selling price of $1.5 million.
O C. The result is not close to the actual selling price of $1.5 million.
Transcribed Image Text:The data show the list and selling prices for several expensive homes. Find the regression equation, letting the the list price be the independent (x) variable. Find the best predicted selling price of a home having a list price of $2 million. Is the result close to the actual selling price of $1.5 million? Use a significance level of 0.05. List price (millions of $) Selling price (millions of $) 2.8 3.4 3.4 2.1 2.4 2.6 2.6 3.6 3.7 1.6 2.1 2.8 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y =+ x (Round to four decimal places as needed.) What is the best predicted selling price of a home having a list price of $2 million? The best predicted selling price for a home having a list price of $2 million is $ (Round to two decimal place as needed.) million. Is the result close to the actual selling price of $1.5 million? O A. The result is close to the actual selling price of $1.5 million. O B. The result is exactly the same as the actual selling price of $1.5 million. O C. The result is not close to the actual selling price of $1.5 million.
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line.
10
3
4
5
8.
7
13
6.
11
12
y 14.74
14.05
4.11
6.46
8.54
13.10 11.85
15.11
10.34 15.14
15.26
y =+ x (Round to two decimal places as needed.)
Create a scatterplot of the data. Choose the correct graph below.
O A.
O B.
С.
D.
Ay
25-
Ay
25
25-
25-
20-
20
20-
20-
153
155
15
155
10
10-
10-
10-
55
53
0-
0.
0.
10 15 20 25
5 10 15 20 25
10 15 20 25
0.
10 15 20 25
Identify a characteristic of the data that is ignored by the regression line.
O A. The data has a pattern that is not a staight line.
B. There is an influential point that strongly affects the graph of the regression line.
C. There is no trend in the data.
D. There is no characteristic of the data that is ignored by the regression line.
Click to select your answer(s).
5
00000000000
Transcribed Image Text:Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. 10 3 4 5 8. 7 13 6. 11 12 y 14.74 14.05 4.11 6.46 8.54 13.10 11.85 15.11 10.34 15.14 15.26 y =+ x (Round to two decimal places as needed.) Create a scatterplot of the data. Choose the correct graph below. O A. O B. С. D. Ay 25- Ay 25 25- 25- 20- 20 20- 20- 153 155 15 155 10 10- 10- 10- 55 53 0- 0. 0. 10 15 20 25 5 10 15 20 25 10 15 20 25 0. 10 15 20 25 Identify a characteristic of the data that is ignored by the regression line. O A. The data has a pattern that is not a staight line. B. There is an influential point that strongly affects the graph of the regression line. C. There is no trend in the data. D. There is no characteristic of the data that is ignored by the regression line. Click to select your answer(s). 5 00000000000
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