A real estate agency collects the data in the following table concerning y = sales price of a house (in thousands of dollars) x1 = home size (in hundreds of square feet) x2 = rating (an overall "niceness rating" for the house expressed on a scale from 1 [worst] to 10 [best], and provided by the real estate agency) Sales Price, y (x $1000) 180 98.1 173.1 136.5 141 165.9 193.5 127.8 163.5 172.5 Home Size, x₁ (x 100 ft²) BERIKANERS Modell: y Bo + B₁x₁ + B₂x₂ + € Model2: y Bo + B₁x₁ + B₂X₂ + B3x² + € 23 11 20 17 15 21 24 13 19 25 Rating, * SNamotora X₂ (b) Interpret the regression coefficients (c) Test significance of each individual coefficients. 5 2 9 3 8 4 7 6 7 The agency wishes to develop a regression model that can be used to predict the sales prices of future houses it will list. 2 Use software of your choice to fit the 2 following models. Then answer the same questions (a-e) for both models. (a) Discuss why scatter plot of y vs x₁ and x₂ indicate that this model might be reasonable. (d) Test overall regression model (e) For an individual house with size=2000 Square feet and rating-8 find point estimation, 95% C.I. and 95% P.I.
A real estate agency collects the data in the following table concerning y = sales price of a house (in thousands of dollars) x1 = home size (in hundreds of square feet) x2 = rating (an overall "niceness rating" for the house expressed on a scale from 1 [worst] to 10 [best], and provided by the real estate agency) Sales Price, y (x $1000) 180 98.1 173.1 136.5 141 165.9 193.5 127.8 163.5 172.5 Home Size, x₁ (x 100 ft²) BERIKANERS Modell: y Bo + B₁x₁ + B₂x₂ + € Model2: y Bo + B₁x₁ + B₂X₂ + B3x² + € 23 11 20 17 15 21 24 13 19 25 Rating, * SNamotora X₂ (b) Interpret the regression coefficients (c) Test significance of each individual coefficients. 5 2 9 3 8 4 7 6 7 The agency wishes to develop a regression model that can be used to predict the sales prices of future houses it will list. 2 Use software of your choice to fit the 2 following models. Then answer the same questions (a-e) for both models. (a) Discuss why scatter plot of y vs x₁ and x₂ indicate that this model might be reasonable. (d) Test overall regression model (e) For an individual house with size=2000 Square feet and rating-8 find point estimation, 95% C.I. and 95% P.I.
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter2: Exponential, Logarithmic, And Trigonometric Functions
Section2.CR: Chapter 2 Review
Problem 111CR: Respiratory Rate Researchers have found that the 95 th percentile the value at which 95% of the data...
Related questions
Question
![A real estate agency collects the data in the following table concerning
y = sales price of a house (in thousands of dollars)
x1 = home size (in hundreds of square feet)
x2 = rating (an overall "niceness rating" for the house expressed on a scale from 1 [worst] to 10
[best], and provided by the real estate agency)
Sales Price,
y (x $1000)
180
98.1
173.1
136.5
141
165.9
193.5
127.8
163.5
172.5
Home Size,
x₁ (x 100 ft²)
Modell: y Bo + B₁x₁ + B₂X₂ +€
Model2: y Bo + B₁x₁ + B₂x₂ + B3x² + €
=
23
11
20
17
15
21
24
13
19
25
Rating,
X₂
Make a comparison between models:
(f) Based on their Råbj
(g) Based on their C.I and P.I.
86966 ∞ WONt
2
9
3
8
4
7
The agency wishes to develop a regression model that can be used to predict the sales prices of
future houses it will list.
2
Use software of your choice to fit the 2 following models. Then answer the same questions (a-e)
for both models.
(a) Discuss why scatter plot of y vs x₁ and x₂ indicate that this model might be
reasonable.
(b) Interpret the regression coefficients
(c) Test significance of each individual coefficients.
(d) Test overall regression model
(e) For an individual house with size=2000 Square feet and rating=8 find point
estimation, 95% C.I. and 95% P.I.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb9e27b5d-0ab8-428e-954d-97d64fc14c61%2F5139ee85-d5f3-4e3b-9af6-8119a7348f8a%2Fcc03luk_processed.png&w=3840&q=75)
Transcribed Image Text:A real estate agency collects the data in the following table concerning
y = sales price of a house (in thousands of dollars)
x1 = home size (in hundreds of square feet)
x2 = rating (an overall "niceness rating" for the house expressed on a scale from 1 [worst] to 10
[best], and provided by the real estate agency)
Sales Price,
y (x $1000)
180
98.1
173.1
136.5
141
165.9
193.5
127.8
163.5
172.5
Home Size,
x₁ (x 100 ft²)
Modell: y Bo + B₁x₁ + B₂X₂ +€
Model2: y Bo + B₁x₁ + B₂x₂ + B3x² + €
=
23
11
20
17
15
21
24
13
19
25
Rating,
X₂
Make a comparison between models:
(f) Based on their Råbj
(g) Based on their C.I and P.I.
86966 ∞ WONt
2
9
3
8
4
7
The agency wishes to develop a regression model that can be used to predict the sales prices of
future houses it will list.
2
Use software of your choice to fit the 2 following models. Then answer the same questions (a-e)
for both models.
(a) Discuss why scatter plot of y vs x₁ and x₂ indicate that this model might be
reasonable.
(b) Interpret the regression coefficients
(c) Test significance of each individual coefficients.
(d) Test overall regression model
(e) For an individual house with size=2000 Square feet and rating=8 find point
estimation, 95% C.I. and 95% P.I.
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