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Square Footage, x 2251 3240 1137 1966 3001 2730 3998 2286 2734 1767 1869 3978 Selling Price ($000s), y 387.4 382.7 191.3 336.6 603.6 363.4 609.9 388.8 444.5 307.2 283.8 715.1

Square Footage, x 2251 3240 1137 1966 3001 2730 3998 2286 2734 1767 1869 3978 Selling Price ($000s), y 387.4 382.7 191.3 336.6 603.6 363.4 609.9 388.8 444.5 307.2 283.8 715.1

Holt Mcdougal Larson Pre-algebra: Student Edition 2012
Holt Mcdougal Larson Pre-algebra: Student Edition 2012
1st Edition
ISBN:9780547587776
Author:HOLT MCDOUGAL
Publisher:HOLT MCDOUGAL
Chapter11: Data Analysis And Probability
Section11.2: Box-and-whisker Plots
Problem 2E
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​(e) Find the​ least-squares regression line treating square footage as the explanatory variable.

Data Table Square Footage, x 2251 3240 1137 1966 3001 2730 3998 2286 2734 1767 1869 3978 Selling Price ($000s), y 387.4 382.7 191.3 336.6 603.6 363.4 609.9 388.8 444.5 307.2 283.8 715.1
Transcribed Image Text:Data Table Square Footage, x 2251 3240 1137 1966 3001 2730 3998 2286 2734 1767 1869 3978 Selling Price ($000s), y 387.4 382.7 191.3 336.6 603.6 363.4 609.9 388.8 444.5 307.2 283.8 715.1
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. 1000- 1000 O No 4000 Yes 150- 1000 4000 (c) Determine the linear correlation coefficient between square footage and asking price. r= 0.900 (Round to three decimal places as needed.) (d) Is there a linear relation between square footage and asking price? C 150 1000 (e) Find the least-squares regression line treating square footage as the explanatory variable. y=x+ (Round the slope to three decimal places as needed. Round the intercept to one decimal place as needed.) 4000 1000 150 750
Transcribed Image Text: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. 1000- 1000 O No 4000 Yes 150- 1000 4000 (c) Determine the linear correlation coefficient between square footage and asking price. r= 0.900 (Round to three decimal places as needed.) (d) Is there a linear relation between square footage and asking price? C 150 1000 (e) Find the least-squares regression line treating square footage as the explanatory variable. y=x+ (Round the slope to three decimal places as needed. Round the intercept to one decimal place as needed.) 4000 1000 150 750
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