According to the inverse regression function and the regression slope and intercept from predicting prices from square-feet, what is the estimated square-feet for a house costing $800,000? You do not need to round your answer.

Question 6Your friend in the U.S. gives you a simple regression fit for predicting house prices from square feet. The estimated intercept is -44850 and the estimated slope is 280.76. You believe that your housing market behaves very similarly, but houses are measured in square meters. To make predictions for inputs in square meters, what slope must you use? Hint: there are 0.092903 square meters in 1 square foot. You do not need to round your answer.1 point

Using your Slope and Intercept from predicting prices from square feet, what is the predicted price for a house with 2650 sqft? Use American-style decimals without comma separators (e.g. 300000.34), and round your answer to 2 decimal places. Do not include the dollar sign. You do not need to round your answer.

Question 41 ptsUse the data given below to answer the following question(s).Following is an extract from the database of a construction company. The table shows the heightof walls in feet and the cost of raising them. The estimated simple linear regression equation isgiven as Ŷ = b0 + b1X. (Hint: Use Excel functions).What is the estimated cost of raising a 10-inch wall?Group of answer choices1505.7861103.578968.61091123.008

An agent for a real estate company in a large city would like to be able to predict the monthly rental cost for apartments,based on the size of the apartment,as defined by square footage.A sample of eight apartments in a neighborhood was selected,and the information gathered revealed the data shown below.For these data,the regression coefficients are bo=373.5333 and b1=0.8553.Complete parts(a)through(d). Monthly Rent($); 9001,500,800,1600,1950,925,1825,1400, Size(Square Feet);850,1300,1050,1100,2000,650,1350,950 a.Determine the coefficient of determination, and interpret its (Round to three decimal places as needed.)

Question 1Assume you fit a regression model to predict house prices from square feet based on a training data set consisting of houses with square feet in the range of 1000 and 2000. In which interval would we expect predictions to do best?