Can you plz answer this as soon as possible. Betty is considering a move to town B and wants to buy a single family home. She has done some research and wants to betterunderstand the relationship between the list price of a home and how big the home is (as measured by the number of squarefeet). Although she has verified that the relationship is roughly linear, Betty doesn't know how to calculate the equation of theleast squares regression line. However, she has determined the following summary statistics from her random sample of 25homes in town B.S = 1146.75I = 2585.2Sy = 128, 614.06j = 411, 515.32r = 0.884b. Based upon the summary statistics shown above, calculate and identify the equation of the least squares regression line.c. Based upon the equations you identified and information provided in parts (a) and (b) above:i. Compare the relationship between the list price of a home in town A and the number of square feet vs. the list priceof a home in town B and the number of square feet.ii. In which town, A or B, is the list price of a home higher per square foot? Explain your answer.d. Researchers are interested in conducting a test for whether the slopes of the two least squares regression lines are equalor not. Assuming the residual variances are not statistically equal, and since both sample sizes are greater than 20, a z-testis appropriate for this situation.i. Given that the standard error for the difference in the two slopes is 33.952, what is the value of the z-statistic?ii. Based on your answer to part (d)(i) above, what is the p-value for the test? PromptAngie is considering a move to town A and wants to buy a single family home. She has done some research and wants to betterunderstand the relationship between the list price of a home and how big the home is (as measured by the number of squarefeet). After randomly selecting 25 homes that are currently on the market in town A and verifying that the relationship is roughlylinear, Angie uses computer software and requests the linear regression comparing price (in dollars) to number of square feet.The computer output is shown below:PredictorConstantCoefSE CoefT103,72082.0519,78817.690.03920.00012.187Square Feet4.637s = 88,163R-Sq = 48.3%R-Sq (Adj) = 46.9%a. Based upon the computer output shown above:i. Identify the equation of the least squares regression line. Define all variables used in the equation.ii. Using the equation of the least squares regression line, predict how much Angie would pay for a home with 1800square feet.Betty is considering a move to town B and wants to buy a single family home. She has done some research and wants to betterunderstand the relationship between the list price of a home and how big the home is (as measured by the number of squarefeet). Although she has verified that the relationship is roughly linear, Betty doesn't know how to calculate the equation of theleast squares regression line. However, she has determined the following summary statistics from her random sample of 25homes in town B.Sz = 1146.75

Given Information: Ange is considering a move to town A. Number of home selected = 25. Computer…

Betty is considering a move to town Band wants to buy a single family home. She has done some research and wants to better understand the relationship between the list price of a home and how big the home is (as measured by the number of square feet). Although she has verified that the relationship is roughly linear, Betty doesn't know how to calculate the equation of the least squares regression line. However, she has determined the following summary statistics from her random sample of 25 homes in town B. S, = 1146.75 * = 2585.2 Sy = 128, 614.06 j = 411,515.32 r = 0.884 b. Based upon the summary statistics shown above, calculate and identify the equation of the least squares regression line. c. Based upon the equations you identified and information provided in parts (a) and (b) above: i. Compare the relationship between the list price of a home in town A and the number of square feet vs. the list price of a home in town B and the number of square feet. ii. In which town, A or B, is the list price of a home higher per square foot? Explain your answer.

Betty is considering a move to town Band wants to buy a single family home. She has done some research and wants to better understand the relationship between the list price of a home and how big the home is (as measured by the number of square feet). Although she has verified that the relationship is roughly linear, Betty doesn't know how to calculate the equation of the least squares regression line. However, she has determined the following summary statistics from her random sample of 25 homes in town B. S, = 1146.75 * = 2585.2 Sy = 128, 614.06 j = 411,515.32 r = 0.884 b. Based upon the summary statistics shown above, calculate and identify the equation of the least squares regression line. c. Based upon the equations you identified and information provided in parts (a) and (b) above: i. Compare the relationship between the list price of a home in town A and the number of square feet vs. the list price of a home in town B and the number of square feet. ii. In which town, A or B, is the list price of a home higher per square foot? Explain your answer.

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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Estimation

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Question

Can you plz answer this as soon as possible.

Betty is considering a move to town B and wants to buy a single family home. She has done some research and wants to better
understand the relationship between the list price of a home and how big the home is (as measured by the number of square
feet). Although she has verified that the relationship is roughly linear, Betty doesn't know how to calculate the equation of the
least squares regression line. However, she has determined the following summary statistics from her random sample of 25
homes in town B.
S = 1146.75
I = 2585.2
Sy = 128, 614.06
j = 411, 515.32
r = 0.884
b. Based upon the summary statistics shown above, calculate and identify the equation of the least squares regression line.
c. Based upon the equations you identified and information provided in parts (a) and (b) above:
i. Compare the relationship between the list price of a home in town A and the number of square feet vs. the list price
of a home in town B and the number of square feet.
ii. In which town, A or B, is the list price of a home higher per square foot? Explain your answer.
d. Researchers are interested in conducting a test for whether the slopes of the two least squares regression lines are equal
or not. Assuming the residual variances are not statistically equal, and since both sample sizes are greater than 20, a z-test
is appropriate for this situation.
i. Given that the standard error for the difference in the two slopes is 33.952, what is the value of the z-statistic?
ii. Based on your answer to part (d)(i) above, what is the p-value for the test?

Prompt
Angie is considering a move to town A and wants to buy a single family home. She has done some research and wants to better
understand the relationship between the list price of a home and how big the home is (as measured by the number of square
feet). After randomly selecting 25 homes that are currently on the market in town A and verifying that the relationship is roughly
linear, Angie uses computer software and requests the linear regression comparing price (in dollars) to number of square feet.
The computer output is shown below:
Predictor
Constant
Coef
SE Coef
T
103,720
82.05
19,788
17.69
0.0392
0.0001
2.187
Square Feet
4.637
s = 88,163
R-Sq = 48.3%
R-Sq (Adj) = 46.9%
a. Based upon the computer output shown above:
i. Identify the equation of the least squares regression line. Define all variables used in the equation.
ii. Using the equation of the least squares regression line, predict how much Angie would pay for a home with 1800
square feet.
Betty is considering a move to town B and wants to buy a single family home. She has done some research and wants to better
understand the relationship between the list price of a home and how big the home is (as measured by the number of square
feet). Although she has verified that the relationship is roughly linear, Betty doesn't know how to calculate the equation of the
least squares regression line. However, she has determined the following summary statistics from her random sample of 25
homes in town B.
Sz = 1146.75

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