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?
Question
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?
Solution
We would expect the predictions to do best in the interval of 1000 to 2000 square feet.
This is because the regression model was trained on data within this range. The model is most accurate for predicting house prices within the range of the data it was trained on.
Think of it like this: if you studied for a history test by learning about events from 1900 to 2000, you would do best on test questions about that time period. You might not do as well on questions about events from 1800 to 1900 or from 2000 to 2100, because you didn't study those periods as much.
In the same way, a regression model does best when making predictions within the range of data it was trained on.
Similar Questions
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
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.
I predict house prices based on multiple features like area, bedrooms, and bathrooms. Which regression method am I?
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.