Predict sale ($thousands) Y based on living space in the house (square feet) (denoted as X1) and whether the house has afireplace (denoted as X2) and house type, three levels, colonial, ranch, and other. We created two dummy variables, X3 andX4, for the categorical variable, house type.X3 equals 1 if house type is colonial, O otherwise;X4 equals 1 if house type is ranch, O otherwise.Yi = Bo+B1X1i + ẞ2X2i + ẞ3X3i + B4X4i + ЄiThe following is the regression results in Excel.InterceptLiving Space (X1)Fireplace (X2)House Type_c (X3)House Type R (X4)Coefficients Standard Erro t StatP-value Lower 95% Upper 95%332.296488 15.062026 22.0618718 2.6897E-29 302.123624 362.4693520.02768425 0.00790811 3.50074144 0.00091821 0.0118424 0.0435261116.2773295 10.4909814 1.55155451 0.1264025 -4.7386316 37.2932906169.377469 13.6483741 12.4100841 1.0402E-17 142.036491 196.71844881.9422133 11.4256387 7.17178402104.8305181.8E-0959.0539085What is the predicted asking price for a house with Living Space 1000 square feet and a fireplace, which type is Ranch.○ 545.64359.98458.20376.26

The regression output table is given in the question.It is required to obtain the predicted asking…

Answered: Predict sale ($thousands) Y based on…

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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Atlantic hurricanes form off the western coast of Africa. As warm moist air rises, it begins to rotate around a low- pressure system. This rotation is sustained by warm ocean temperatures and a central low pressure. Once a sustained wind speed of 74 miles per hour is reached, the storm is considered a hurricane. As man-made climate change continues to increase the temperature of the Earth's oceans, it is expected that the strength of hurricanes will Typically, a lower central pressure within a hurricane's eye is associated with a higher wind speed. Here, statistical software (R/RStudio) will be used to explore this relationship by applying linear regression methods. Using a database of landfalling hurricanes in the United States, a linear regression will be used to correlate the central pressure of each hurricane to its maximum sustained wind speed. increase. Regression Plot y=942.196-0.884*x R^2=0.768 ----- ----------- -. •... •. 980 1000 940 960 900 920 Independent Variable (x)…
Suppose you have access to a database with the variables listed below. Choose two variables you are interested in exploring that may be related (a predictor and outcome). Which variable is your y (outcome) and which is your x (predictor)? *Hint: which one may predict the other? Example: hot weather may predict sunburns.
Let Q,, Q2 and Q, be dummy variables with the value 1 indicating observations are from first, second and third quarters and the value 0 otherwise, respectively. If the investigator estimates company sale measured in million dollars as sale = 4+ 20, +2.5Q2 +30,, then the investigator: O a. forecasts sale for the first quarter to be 3.5 m$. O b. forecasts sale for the first quarter to be 3 m$. O c. forecasts sale for the first quarter to be 1 m$. O d. forecasts sale for the last quarter to be 8.5 m$. e. forecasts sale for the last quarter to be 4 m$.
Please help me better understand word problem. A researcher was investigating variables that might be associated with the academic performance of high school students. The data included the average Math SAS score of all high school seniors in the city that took the exam (labeled as the variable SAT-M), the average number of dollars per pupil spent on education by the city (labeled as the variable $Per Pupil), and the percentage of high school seniors in the city that took the exam (labeled as the variable %Taking). As part of the researcher's investigation, he ran the following multiple linear regression model as SAT-M=Beta0 + Beta1($Per Pupil) + Beta2(%Taking). This model was fit to the data using the method of least-squares, results shown inside of table within photo. Question: What's the 95% confidence interval for Beta1, (coefficient of variable $PerPupil). Then determine the interpretation for Beta2 (coefficient of %Taking variable).
The residents of a housing development for senior citizens have completed a survey whereon they indicated how physically active they are and how many visitors they receive each week. Are these two varibles related for the 10 cases reported below?
During 10 weeks, a dealership recorded the number of TV ads (x variable) and the number of cars sold (y variable). The results are given in the following table. X 6 20 0 14 25 16 28 18 10 8 Y 15 31 10 16 28 20 40 25 12 15 Please asnwer questions on picture thank you
3) Use y = -x + 5 to fill in the missing ordered pairs on the table below. y 8 10 -4 5 2.
The level of water usage of 250 houses was rated in a survey as low, medium or high and the size of the houses as small, standard or large. The variables,level of water usage and size of house, as recorded in this survey, are a. both numerical variables. b. both categorical variables. c. neither numerical nor categorical variables. d. numerical and categorical variables respectively.
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