Reasons for Modeling: Extrapolation
Another common use of modeling is extrapolation to estimate data values "outside" or "beyond" the range (min and max values of time
) of the measured data. In this exercise, we have measured distances for times 0 through 5 hours, but we are interested in estimating how far we'd go in 8 hours. Using the same data set from the previous exercise, we have prepared a linear model distance = model(time)
. Use that model()
to make a prediction about the distance traveled for a time much larger than the other times in the measurements.
This exercise is part of the course
Introduction to Linear Modeling in Python
Exercise instructions
- Use
distance = model(time)
to extrapolate beyond the measured data totime=8
hours. - Print the
distance
predicted and then check whether it is less than or equal to400
. - If your car can travel, at most,
400
miles on a full tank, and it takes 8 hours to drive home, will you make it without refilling? You should haveanswer=True
if you'll make it, oranswer=False
if you will run out of gas.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Select a time not measured.
time = 8
# Use the model to compute a predicted distance for that time.
distance = model(____)
# Inspect the value of the predicted distance traveled.
print(distance)
# Determine if you will make it without refueling.
answer = (____ <= 400)
print(answer)