Question 5Your 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 intercept must you use? Hint: there are 0.092903 square meters in 1 square foot. You do not need to round your answer.
Question
Question 5Your 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 intercept must you use? Hint: there are 0.092903 square meters in 1 square foot. You do not need to round your answer.
Solution
The intercept in the regression model doesn't change when we convert from square feet to square meters. This is because the intercept is the estimated house price when the size of the house is zero. So, whether we measure the size of the house in square feet or square meters, the price of a house with zero size remains the same.
Therefore, the intercept you must use to make predictions for inputs in square meters is the same as the intercept given for the model in square feet, which is -44850.
Similar Questions
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 1Using 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 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?
Two people present you with fits of their simple regression model for predicting house prices from square feet. You discover that the estimated intercept and slopes are exactly the same. This necessarily implies that these two people fit their models on exactly the same data set. 1 pointTrueFalse
You have a data set consisting of the sales prices of houses in your neighborhood, with each sale time-stamped by the month and year in which the house sold. You want to predict the average value of houses in your neighborhood over time, so you fit a simple regression model with average house price as the output and the time index (in months) as the input. Based on 10 months of data, the estimated intercept is $4569 and the estimated slope is 143 ($/month). If you extrapolate this trend forward in time, at which time index (in months) do you predict that your neighborhood's value will have doubled relative to the value at month (index) 10?Please enter a number below, round to the nearest month.
Upgrade your grade with Knowee
Get personalized homework help. Review tough concepts in more detail, or go deeper into your topic by exploring other relevant questions.