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(a) Which variable is the explanatory variable? Square Footage O Selling Price (b) Draw a scatter diagram of the data. Choose the correct scatter diagram below. OA. 4000- 1000+ 150 700 B. 700- 150 1000 ●● 4000 (Round to three decimal places as needed.) C. 700- 150+ 1000 4000 Q O D. (c) Determine the linear correlation coefficient between square footage and asking price. 4000- 1000- 1000 4000

(a) Which variable is the explanatory variable? Square Footage O Selling Price (b) Draw a scatter diagram of the data. Choose the correct scatter diagram below. OA. 4000- 1000+ 150 700 B. 700- 150 1000 ●● 4000 (Round to three decimal places as needed.) C. 700- 150+ 1000 4000 Q O D. (c) Determine the linear correlation coefficient between square footage and asking price. 4000- 1000- 1000 4000

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Square Footage, x 2192 3178 1077 2026 3105 2860 3944 2150 2507 1707 1699 3718 Selling Price ($000s), y 378.1 373.7 181.9 346 621.5 383.6 601.1 367.4 409.1 298.1 257.3 675.2
Transcribed Image Text:Square Footage, x 2192 3178 1077 2026 3105 2860 3944 2150 2507 1707 1699 3718 Selling Price ($000s), y 378.1 373.7 181.9 346 621.5 383.6 601.1 367.4 409.1 298.1 257.3 675.2
11:59 K One of the biggest factors in determining the value of a home is the square footage. The accompanying data represent the square footage and selling price (in thousands of dollars) for a random sample of homes for sale in a certain region. Complete parts (a) through (h) below. Click the icon to view the housing data. (a) Which variable is the explanatory variable? Square Footage Selling Price (b) Draw a scatter diagram of the data. Choose the correct scatter diagram below. A. Ax 4000- 1000- 150 ●● · • Yes No ● 700 B. Ay 700- 150+ 1000 H 4000 Q Ау (Round to three decimal places as needed.) (d) Is there a linear relation between square footage and asking price? ||| 700- (c) Determine the linear correlation coefficient between square footage and asking price. = 150+ 1000 O A. No-a house of square feet is not possible. (Type an integer or a simplified fraction.) H OB. For a house that is sold for $0, the predicted square footage is (Round to three decimal places as needed.) OC. For a house that is 0 square feet, the predicted selling price is (Round to three decimal places as needed.) OD. For every additional square foot, the selling price increases by (Round to three decimal places as needed.) OE. It is not appropriate to interpret the slope. The home's price is thousand. (Round to the nearest whole number as needed.) Vol 4G 40% LTE2 (e) Find the least-squares regression line treating square footage as the explanatory variable. ŷ=x+ (Round the slope to three decimal places as needed. Round the intercept to one decimal place as needed.) OA. For every additional thousand dollars in selling price, the square footage increases by average. (Round to three decimal places as needed.) 4000 (f) Interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. OD. No-a house of square feet is outside the scope of the model (Type an integer or a simplified fraction.) O E. More information about the houses is necessary before deciding. O OC. Yes-a house of square feet is possible and within the scope of the model. (Type an integer or a simplified fraction.) D. 4000- OB. No-a house of square feet is not possible and outside the scope of the model. (Type an integer or a simplified fraction.) 1000- Ay thousand dollars. (g) Is it reasonable to interpret the y-intercept? Why? Select the correct choice below and, if necessary, fill in the answer box to complete your choice. 1000 thousand dollars, on average. (h) One home that is 1477 square feet is sold for $225 thousand. Is this home's price above or below average for a home of this size? 4000 square feet, on the average price. The average price of a home that is 1477 square feet is $
Transcribed Image Text:11:59 K One of the biggest factors in determining the value of a home is the square footage. The accompanying data represent the square footage and selling price (in thousands of dollars) for a random sample of homes for sale in a certain region. Complete parts (a) through (h) below. Click the icon to view the housing data. (a) Which variable is the explanatory variable? Square Footage Selling Price (b) Draw a scatter diagram of the data. Choose the correct scatter diagram below. A. Ax 4000- 1000- 150 ●● · • Yes No ● 700 B. Ay 700- 150+ 1000 H 4000 Q Ау (Round to three decimal places as needed.) (d) Is there a linear relation between square footage and asking price? ||| 700- (c) Determine the linear correlation coefficient between square footage and asking price. = 150+ 1000 O A. No-a house of square feet is not possible. (Type an integer or a simplified fraction.) H OB. For a house that is sold for $0, the predicted square footage is (Round to three decimal places as needed.) OC. For a house that is 0 square feet, the predicted selling price is (Round to three decimal places as needed.) OD. For every additional square foot, the selling price increases by (Round to three decimal places as needed.) OE. It is not appropriate to interpret the slope. The home's price is thousand. (Round to the nearest whole number as needed.) Vol 4G 40% LTE2 (e) Find the least-squares regression line treating square footage as the explanatory variable. ŷ=x+ (Round the slope to three decimal places as needed. Round the intercept to one decimal place as needed.) OA. For every additional thousand dollars in selling price, the square footage increases by average. (Round to three decimal places as needed.) 4000 (f) Interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. OD. No-a house of square feet is outside the scope of the model (Type an integer or a simplified fraction.) O E. More information about the houses is necessary before deciding. O OC. Yes-a house of square feet is possible and within the scope of the model. (Type an integer or a simplified fraction.) D. 4000- OB. No-a house of square feet is not possible and outside the scope of the model. (Type an integer or a simplified fraction.) 1000- Ay thousand dollars. (g) Is it reasonable to interpret the y-intercept? Why? Select the correct choice below and, if necessary, fill in the answer box to complete your choice. 1000 thousand dollars, on average. (h) One home that is 1477 square feet is sold for $225 thousand. Is this home's price above or below average for a home of this size? 4000 square feet, on the average price. The average price of a home that is 1477 square feet is $
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