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 26 minutes. How does the result compare to the actual tip amount of $5.46? Distance Time Fare Tip 0.68 1.80 1.65 1.02 6.00 25.00 11.00 6.30 16.30 9.80 1.89 1.50 1.96 1.40 0.49 12.71 8.00 18.00 2.00 27.00 18.00 7.80 12.30 4.80 36.80 14.30 2.34 2.46 0.00 0.00 4.29 2.47 O ... The regression equation is y=+x. X. (Round the y-intercept to two decimal places as needed. Round the slope to four decimal places as needed.)

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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 26 minutes. How does the result
compare to the actual tip amount of $5.46?
Distance 0.68 1.80
6.00 25.00
6.30 16.30
9.80
1.89 1.50 1.96
Time
Fare
Tip
1.65
11.00
1.02
1.40
0.49
12.71 2.47
8.00 18.00
2.00 27.00 18.00
7.80 12.30
4.80 36.80
14.30
2.34 2.46 0.00 0.00
4.29
D
The regression equation is y=[ +
(Round the y-intercept to two decimal places as needed. Round the slope to four decimal places as needed.)
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 26 minutes. How does the result compare to the actual tip amount of $5.46? Distance 0.68 1.80 6.00 25.00 6.30 16.30 9.80 1.89 1.50 1.96 Time Fare Tip 1.65 11.00 1.02 1.40 0.49 12.71 2.47 8.00 18.00 2.00 27.00 18.00 7.80 12.30 4.80 36.80 14.30 2.34 2.46 0.00 0.00 4.29 D The regression equation is y=[ + (Round the y-intercept to two decimal places as needed. Round the slope to four decimal places as needed.)
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