Sean is hiking the Appalachinn Trail from Georgia to Maine. The distance of his hike is 2200 miles. It took Sean 134 days to complete the hike. The data below represent the distance, D, he had hiked t days after the start of his trip. 19 34 67 91 112 134 DO 308 578 1070 1715 1902 2200 1. Determine the linear regression equation for this data. Linear Regression Equation: D = Round to the nearest tenth as needed. 2. Interpret the meaning of the slope of this regression model. Sean hiked at a rate of approximately Select an answer v 3. Use your linear regression equation to estimate the total number of miles Sean had hiked in 63 days. Round your answer to the nearest mile. In 63 days, Sean had hiked miles. 4. Use your linear regression equation to estimate the total number of days it took for Sean to hike 309 miles. Round your answer to the nearest day. In days, Sean had hiked 309 miles.
Sean is hiking the Appalachinn Trail from Georgia to Maine. The distance of his hike is 2200 miles. It took Sean 134 days to complete the hike. The data below represent the distance, D, he had hiked t days after the start of his trip. 19 34 67 91 112 134 DO 308 578 1070 1715 1902 2200 1. Determine the linear regression equation for this data. Linear Regression Equation: D = Round to the nearest tenth as needed. 2. Interpret the meaning of the slope of this regression model. Sean hiked at a rate of approximately Select an answer v 3. Use your linear regression equation to estimate the total number of miles Sean had hiked in 63 days. Round your answer to the nearest mile. In 63 days, Sean had hiked miles. 4. Use your linear regression equation to estimate the total number of days it took for Sean to hike 309 miles. Round your answer to the nearest day. In days, Sean had hiked 309 miles.
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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Transcribed Image Text:LINEAR REGRESSION
Sean is hiking the Appalachian Trail from Georgia to Maine. The distance of his hike is 2200 miles. It
took Sean 134 days to complete the hike. The data below represent the distance, D, he had hiked t
days after the start of his trip.
19
34
67
91
112
134
D()
308
578
1070
1715
1902
2200
1. Determine the linear regression equation for this data.
Linear Regression Equation: D =
Round to the nearest tenth as needed.
2. Interpret the meaning of the slope of this regression model.
Sean hiked at a rate of approximately
Select an answer v
3. Use your linear regression equation to estimate the total number of miles Sean had hiked in 63
days. Round your answer to the nearest mile.
In 63 days, Sean had hiked
miles.
4. Use your linear regression equation to estimate the total number of days it took for Sean to hike
309 miles. Round your answer to the nearest day.
In
days, Sean had hiked 309 mniles.
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Transcribed Image Text:Linear Regression - Christmas Trees
The following table gives the total number of live Christmas trees sold, in millions, in the United
States from 2004 to 2011. (Source: Statista.com).
t=number of years since
2004
C= total number of
2
4
6
17
Christmas trees sold in the
27.1
28.6
28.2
27
30.8
U.S. (in millions)
1. Use the TABLE to determine the number of live Christmas trees sold in the year 2008.
In 2008, there were approximately
million live Christmas trees sold in the
U.S.
2. Determine the linear regression equation that models the set of data above. Use the indicated
variables and proper function notation. Round to the nearest hundredth as needed.
C =
3. Interpret the meaning of the slope of your (rounded) regression model.
From 2004 to 2011, the number of Christmas trees sold in the U.S. increased by
approximately
million trees each year.
4. Use the REGRESSION EQUATION to determine the number of live Christmas trees sold in the
year 2008.
In 2008, there were approximately
million live Christmas trees sold in the
US.
5. Your answers to parts 1 and 4 should be different. Why is this the case?
O The data are not perfectly linear. The regression equation gives a more precise answer than
the value from the table.
O The data are linear. The regression equation gives a more precise answer than the value
from the table.
O The data are not perfectly linear. The regression equation gives only an approximation of
the actual value, not the exact value.
O The data are linear. The regression equation gives only an approximation of the actual
value, not the exact value.
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