Below is some of the regression output from a regression of the amount rental houses on an island rent for (expressed in thousands of S's) based on the size of the house (expressed in square feet), whether the house has an ocean front view (VIEW = 1 if it has an ocean front view and = 0 if not), and an interaction term between the ocean front view dummy variable and the size of the house. If the estimated equation is: Price = 1,474 + 0.31*Size + 1,885*View + 0.1"(Size*View) Suppose you just built a house with an ocean front view that is 3900 square feet and you want to decide how much to rent it for. What is the predicted price of a house that is 3900 square feet and has an ocean front view? (please express your answer using 1 decimal places)

Below is some of the regression output from a regression of the amount rental houses on an island rent for (expressed in thousands of S's) based on the size of the house (expressed in square feet), whether the house has an ocean front view (VIEW = 1 if it has an ocean front view and = 0 if not), and an interaction term between the ocean front view dummy variable and the size of the house. If the estimated equation is: Price = 1,474 + 0.31Size + 1,885View + 0.1"(Size*View) Suppose you just built a house with an ocean front view that is 3900 square feet and you want to decide how much to rent it for. What is the predicted price of a house that is 3900 square feet and has an ocean front view? (please express your answer using 1 decimal places)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

what is the answer?
This question has do with linear regression.If I consider attendance in a class versus final grade in the class can you explain where there is a positive and when there is a negative relationship between them.
Daphne, who graduated from one of the prestigious schools in Cebu, was asked by her boss to estimate the demand of the customer for the succeeding month. The resulting estimated regression equation is y = 1.304 + 0.602x, with the following range of independent variables: 0, 5, 8, 13, 16, 18, and 23. How will her boss interpret the estimated intercept?
A researcher wanted to predict the sodium content (in milligrams) of beef hot dogs by looking at the calorie content. His findings from a sample of 10 beef hot dogs are summarized below. The regression equation for his data is ŷ= -299.48 + 4.35 x Calories 186 181 176 149 184 190 158 139 175 148 Sodium 495 477 425 322 482 587 370 322 479 375 Interpret the slope in terms of this problem. If appropriate, find the sodium content if the calorie content is 170. If not, why? If appropriate, find the sodium content if the calorie content is 136. If not, why?
Please no written by hand solutions 3. A researcher is interested in the correlation between a person’s age and the amount of sleep they get. He uses a poll to collect representative data for 2,000 people. The researcher performs a regression, with a dependent variable of minutes per week spent sleeping, and an independent variable of age in years. The regression results are as follows: - (Intercept): 150 - age: -5 Answer the following: - What is the regression line? - What is the predicted number of minutes sleeping for someone who is 20 years old? - The researcher is also interested in the relationship between age, sleep, and politics. Each person who responds to the poll chooses a value for liberal between 0 (very conservative) and 100 (very liberal) to describe their politics. The researcher performs a regression with the same independent variable of minutes per week sleeping, and dependent variables of age and liberal. The regression results are as follows: - (Intercept):…
A researcher that there is a linear association between the level of potassium content (y) in milligrams and the amount of fiber (x) in grams in cereal. The regression line for the data is computed to y=37+28x rate. It was also computed that r=.59 A. What does the value . 59 tell you? B. What does the value 37 tell you? C. What does the value 28 tell you ? 2. For the line in question 1 what percentage of variability in potassium can be explained by variability in fiber?
Which of the slopes matches best with the slope of the data in the scatter plot? would it be m = 3/8?, m = 8/3?, m = - 3/8? or would it be m = - 8/3???
The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.
Ariel was running analyses over and over in census data and came across a correlation between weight and debt (r=.78). Independent variable is weight and dependent variable is debt. b) Curious Ariel noted some statistics on these weight (M=160lb, SD=15lb) and debt (M=196k, SD=20k). If Ariel wanted to calculate a regression equation, what would her slope and intercept be?
Hello! Please analyse the table 3 and 4 in the image attached. the data is supposed to see if there is a relationship between the prevalence of obesity(table3) or life expectancy (table4) between males and females. thank you!
The following table shows the number of hours of safety training at a large industrial plant for each of 6 divisions within the plant and the number of work hours lost due to accidents. X: Hours of safety training 10 19 30 50 65 80 Y: Work hours lost 80 65 68 35 10 12 a. Determine the Pearson's Coefficient of Correlation for the given data. Answer rounded to two decimal places b. Which of the following is an apporpriate comment for the correlation between X and Y? There is a strong positive correlation between X and Y There is a moderate positive correlation between X and Y There is a weak positive correlation between X and Y There is a strong negative correlation between X and Y There is a moderate negative correlation between X and Y
I just need the d section