MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Question
Answer all parts of question please, thank you!
Does it seem that the trend is linear, or is there a noticeable curve?
The linear model
appropriate because there is a
trend in the data.
Find the equation for predicting time (in hours) from miles (in thousands).
Predicted Time + (Thousand Miles
=
(Round to two decimal places as needed.)
Interpret the slope in the context of the problem. Select the correct choice below and fill in the answer box to complete your choice.
(Round to two decimal places as needed.)
OA. For every additional thousand miles, on average, the time goes up by
hours.
B. For every additional hour, on average, the number of miles goes up by
thousand.
Interpret the intercept in the context of the problem. Although there are no flights with a distance of zero, try to explain what might cause the added time that the intercept represents.
(Round to two decimal places as needed.)
OA. A trip of zero hours would be about
OB. A trip of zero miles would take about
thousand miles. However, a trip would never take exactly zero hours, so these extra miles might account for when the plane taxis the runway
hours. However, a trip would never be exactly zero miles, so this time might account for delays in taking off and landing.
Using the regression line, how long should it take to fly nonstop 3000 miles?
It would take, on average, about hours to fly 3000 miles.
(Round to two decimal places as needed.)
expand button
Transcribed Image Text:Does it seem that the trend is linear, or is there a noticeable curve? The linear model appropriate because there is a trend in the data. Find the equation for predicting time (in hours) from miles (in thousands). Predicted Time + (Thousand Miles = (Round to two decimal places as needed.) Interpret the slope in the context of the problem. Select the correct choice below and fill in the answer box to complete your choice. (Round to two decimal places as needed.) OA. For every additional thousand miles, on average, the time goes up by hours. B. For every additional hour, on average, the number of miles goes up by thousand. Interpret the intercept in the context of the problem. Although there are no flights with a distance of zero, try to explain what might cause the added time that the intercept represents. (Round to two decimal places as needed.) OA. A trip of zero hours would be about OB. A trip of zero miles would take about thousand miles. However, a trip would never take exactly zero hours, so these extra miles might account for when the plane taxis the runway hours. However, a trip would never be exactly zero miles, so this time might account for delays in taking off and landing. Using the regression line, how long should it take to fly nonstop 3000 miles? It would take, on average, about hours to fly 3000 miles. (Round to two decimal places as needed.)
The accompanying table gives the distance from a particular city to seven other cities (in thousands of miles) and gives the time for one randomly chosen, commercial airplane to make that flight. Do
a complete regression analysis that includes a scatterplot with the line, interprets the slope and intercept, and predicts how much time a nonstop flight from this city would take to another city that is
located 3000 miles away.
Click the icon to view the distances and flight times.
Draw a scatterplot for the round-trip flight data. Be sure that distance is the x-variable and time is the y-variable, because time is being predicted from distance. Graph the best-fit line using
technology. Choose the correct scatterplot below.
OA.
Time (hours)
a
OB.
3.5
Distance (1000s of mi)
0-
3.5
Distance (1000s of mi)
Does it seem that the trend is linear, or is there a noticeable curve?
Q
C.
Q
G
3.5
Distance (1000s of mi)
D.
Q
a
3.5
Distance (1000s of mi)
G
The linear model
appropriate because there is a
trend in the data.
Flight Data
Find the equation for predicting time (in hours) from miles (in thousands).
City
Distance
Time
Predicted Time=+Thousand Miles
(1000s of miles) (hours)
(Round to two decimal places as needed.)
1
1.154
2.77
2
Interpret the slope in the context of the problem. Select the correct choice below and fill in the answer box to complete your choice.
(Round to two decimal places as needed.)
2.835
6.14
3
3.373
7.27
4
1.712
4.23
OA. For every additional thousand miles, on average, the time goes up by
OB. For every additional hour on average the number of miles ones un hu
hours.
5
2.447
5.05
thousand
6
1.815
4.24
7
0.232
1.23
expand button
Transcribed Image Text:The accompanying table gives the distance from a particular city to seven other cities (in thousands of miles) and gives the time for one randomly chosen, commercial airplane to make that flight. Do a complete regression analysis that includes a scatterplot with the line, interprets the slope and intercept, and predicts how much time a nonstop flight from this city would take to another city that is located 3000 miles away. Click the icon to view the distances and flight times. Draw a scatterplot for the round-trip flight data. Be sure that distance is the x-variable and time is the y-variable, because time is being predicted from distance. Graph the best-fit line using technology. Choose the correct scatterplot below. OA. Time (hours) a OB. 3.5 Distance (1000s of mi) 0- 3.5 Distance (1000s of mi) Does it seem that the trend is linear, or is there a noticeable curve? Q C. Q G 3.5 Distance (1000s of mi) D. Q a 3.5 Distance (1000s of mi) G The linear model appropriate because there is a trend in the data. Flight Data Find the equation for predicting time (in hours) from miles (in thousands). City Distance Time Predicted Time=+Thousand Miles (1000s of miles) (hours) (Round to two decimal places as needed.) 1 1.154 2.77 2 Interpret the slope in the context of the problem. Select the correct choice below and fill in the answer box to complete your choice. (Round to two decimal places as needed.) 2.835 6.14 3 3.373 7.27 4 1.712 4.23 OA. For every additional thousand miles, on average, the time goes up by OB. For every additional hour on average the number of miles ones un hu hours. 5 2.447 5.05 thousand 6 1.815 4.24 7 0.232 1.23
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