Use the time/tip data from the table below, which includes data from New York City taxi rides. (The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars.) Find the regression equation, letting time be the predictor (x) variable. Find the best predicted tip for a ride that takes 20 minutes. How does the result compare to the actual tip amount of $4.55? Distance 0.68 2.47 12.71 1.80 1.02 8.51 1.32 1.40 Time 6.00 18.00 27.00 25.00 8.00 31.00 8.00 18.00 31.75 7.80 12.30 Fare 6.30 14.30 36.80 16.30 7.80 Tip 1.89 4.29 0.00 1.50 2.34 2.98 0.00 2.46 The regression equation is y=+x. (Round the y-intercept to two decimal places as needed. Round the slope to four decimal places as needed.) The best predicted tip for a ride that takes 20 minutes is $ (Round to the nearest cent as needed.) How does the result compare to the actual tip amount of $4.55? O A. The best predicted value is close to the actual tip of $4.55. O B. The best predicted value is very different from the actual tip of $4.55 O C. The best predicted value is exactly the same as the actual tip of $4.55. O D. The result does not make sense given the context of the data.
Use the time/tip data from the table below, which includes data from New York City taxi rides. (The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars.) Find the regression equation, letting time be the predictor (x) variable. Find the best predicted tip for a ride that takes 20 minutes. How does the result compare to the actual tip amount of $4.55? Distance 0.68 2.47 12.71 1.80 1.02 8.51 1.32 1.40 Time 6.00 18.00 27.00 25.00 8.00 31.00 8.00 18.00 31.75 7.80 12.30 Fare 6.30 14.30 36.80 16.30 7.80 Tip 1.89 4.29 0.00 1.50 2.34 2.98 0.00 2.46 The regression equation is y=+x. (Round the y-intercept to two decimal places as needed. Round the slope to four decimal places as needed.) The best predicted tip for a ride that takes 20 minutes is $ (Round to the nearest cent as needed.) How does the result compare to the actual tip amount of $4.55? O A. The best predicted value is close to the actual tip of $4.55. O B. The best predicted value is very different from the actual tip of $4.55 O C. The best predicted value is exactly the same as the actual tip of $4.55. O D. The result does not make sense given the context of the data.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:Use the time/tip data from the table below, which includes data from New York City taxi rides. (The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars.) Find the regression equation, letting time be the predictor (x) variable. Find the best predicted tip for a ride that takes 20
minutes. How does the result compare to the actual tip amount of $4.55?
Distance 0.68 2.47 12.71 1.80 1.02 8.51 1.32 1.40
6.00 18.00 27.00 25.00 8.00 31.00 8.00 18.00
6.30 14.30 36.80 16.30 7.80 31.75 7.80 12.30
1.89 4.29 0.00 1.50 2.34 2.98 0.00 2.46
Time
Fare
Tip
The regression equation is y=+
X
(Round the y-intercept to two decimal places as needed. Round the slope to four decimal places as needed.)
The best predicted tip for a ride that takes 20 minutes is $
(Round to the nearest cent as needed.)
How does the result compare to the actual tip amount of $4.55?
O A. The best predicted value is close to the actual tip of $4.55.
O B. The best predicted value is very different from the actual tip of $4.55.
O C. The best predicted value is exactly the same as the actual tip of $4.55.
O D. The result does not make sense given the context of the data.
C
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