Question

JetBlue Airlines Revenue, 2008–2015 (millions) Year Revenue Year Revenue 2008 3,388 2012 4,982 2009 3,286 2013...

JetBlue Airlines Revenue,
2008–2015 (millions)
Year Revenue Year Revenue
2008 3,388 2012 4,982
2009 3,286 2013 5,441
2010 3,779 2014 5,817
2011 4,504 2015 6,416

Click here for the Excel Data File

(a) Use Excel, MegaStat, or MINITAB to fit both a linear and an exponential trend to the time series. (Round your answers to 2 decimal places.)

Linear yt =  t +
Exponential yt =  e  t


(b) Make annual forecasts for 2016–2018, using the linear and exponential trend models. (Do not round the intermediate calculations. Round your final answers to 2 decimal places.)

t Linear Exponential
9
10
11
Math   Statistics-And-Probability   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #1

(a) The regression is done using Excel. For linear regression, the equation to be fitted is:

For exponential regression, the equation to be fitted is:

t is the time difference from the base year of 2007. This means that 2008 corresponds to t=1 and 2015 corresponds to t=8.

The regression gives the following equations:

Linear
Exponential

(b) Substituting t=9, 10, and 11 in the model equations give:

Time Linear Exponential
9 6807.79 7220.20
10 7275.82 7990.95
11 7743.86 8843.97
0 0
Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
JetBlue Airlines Revenue, 2008–2015 (millions) Year Revenue Year Revenue 2008 3,388 2012 4,982 2009 3,286 2013...
JetBlue Airlines Revenue, 2008–2015 (millions) Year Revenue Year Revenue 2008 3,388 2012 4,982 2009 3,286 2013 5,441 2010 3,779 2014 5,817 2011 4,504 2015 6,416 (a) Use Excel, MegaStat, or MINITAB to fit both a linear and an exponential trend to the time series. (Round your answers to 2 decimal places.) Linear yt =  t + Exponential yt =  e  t (b) Make annual forecasts for 2016–2018, using the linear and exponential trend models. (Do not round the intermediate calculations. Round your final...
U.S. Civilian Labor Force, 2007-2016 Year Labor Force 2007 153,918 2008 154,655 2009 153,111 2010 153,650...
U.S. Civilian Labor Force, 2007-2016 Year Labor Force 2007 153,918 2008 154,655 2009 153,111 2010 153,650 2011 153,995 2012 155,628 2013 155,151 2014 156,238 2015 157,957 2016 159,640 (d) Make forecasts using the following fitted trend models for years 2017-2019. (Round your answers to the nearest whole number.) t Linear Quadratic Exponential 11 158608 161301 12 159192 163354 13 159776 165653
U.S. Civilian Labor Force (thousands) Year Labor Force Year Labor Force 2007 153,918 2012 155,628 2008...
U.S. Civilian Labor Force (thousands) Year Labor Force Year Labor Force 2007 153,918 2012 155,628 2008 154,655 2013 155,151 2009 153,111 2014 156,238 2010 153,650 2015 157,957 2011 153,995 2016 159,640 Click here for the Excel Data File (a) Make a line graph of the U.S. civilian labor force data. Line Graph A Line Graph B Line Graph C Line Graph D Line Graph A Line Graph B Line Graph C Line Graph D (b) Describe the trend (if any)...
U.S. Civilian Labor Force (thousands) Year Labor Force Year Labor Force 2007 153,918 2012 155,628 2008...
U.S. Civilian Labor Force (thousands) Year Labor Force Year Labor Force 2007 153,918 2012 155,628 2008 154,655 2013 155,151 2009 153,111 2014 156,238 2010 153,650 2015 157,957 2011 153,995 2016 159,640 Click here for the Excel Data File (a) Make a line graph of the U.S. civilian labor force data. Line Graph A Line Graph B Line Graph C Line Graph D Line Graph A Line Graph B Line Graph C Line Graph D (b) Describe the trend (if any)...
U.S. Manufactured General Aviation Shipments, 2009–2015 Year Qtr 1 Qtr 2 Qtr 3 Qtr 4 Total...
U.S. Manufactured General Aviation Shipments, 2009–2015 Year Qtr 1 Qtr 2 Qtr 3 Qtr 4 Total 2009 301 404 395 471 1,571 2010 234 361 272 420 1,287 2011 266 287 286 468 1,307 2012 320 353 337 509 1,519 2013 328 414 346 517 1,605 2014 335 371 378 529 1,613 2015 287 353 362 560 1,562 (c) Use MegaStat or Minitab to calculate estimated seasonal indexes and trend. (Round your answers to 3 decimal places.) Qtr1 Index   ...
The following table shows a company's annual revenue (in billions of dollars) for 2009 to 2014....
The following table shows a company's annual revenue (in billions of dollars) for 2009 to 2014. Year Period (t) Revenue ($ billions) 2009 1 23.7 2010 2 29.3 2011 3 38.0 2012 4 50.2 2013 5 59.7 2014 6 66.7 (a) Develop a linear trend equation for this time series to forecast revenue (in billions of dollars). (Round your numerical values to three decimal places.) Tt = (b)What is the average revenue increase per year (in billions of dollars) that...
The following table shows a company's annual revenue (in billions of dollars) for 2009 to 2014....
The following table shows a company's annual revenue (in billions of dollars) for 2009 to 2014. Year Period (t) Revenue ($ billions) 2009 1 23.6 2010 2 29.3 2011 3 37.8 2012 4 50.2 2013 5 59.8 2014 6 66.6 (a) Construct a time series plot.    What type of pattern exists in the data? The time series plot shows an upward linear trend. The time series plot shows a downward curvilinear trend.      The time series plot shows an upward...
The following table shows a company's annual revenue (in billions of dollars) for 2009 to 2014....
The following table shows a company's annual revenue (in billions of dollars) for 2009 to 2014. Year Period (t) Revenue ($ billions) 2009 1 23.8 2010 2 29.4 2011 3 37.9 2012 4 50.3 2013 5 59.9 2014 6 66.6 (b) Develop a linear trend equation for this time series to forecast revenue (in billions of dollars). (Round your numerical values to three decimal places.) Tt = 12.56+9.154t    (c) What is the average revenue increase per year (in billions...
Year Month Return Year Month Return 2006     Jan 3.95 2008     Jul 3.29 2006     Feb 3.77 2008...
Year Month Return Year Month Return 2006     Jan 3.95 2008     Jul 3.29 2006     Feb 3.77 2008     Aug 4.62 2006     Mar 5.29 2008     Sep 4.81 2006     Apr 3.77 2008     Oct 5.16 2006     May 4.47 2008     Nov 3.69 2006     Jun 5.2 2008     Dec 5.15 2006     Jul 3.9 2009     Jan 5.29 2006     Aug 4.33 2009     Feb 3.19 2006     Sep 4.41 2009     Mar 3.89 2006     Oct 5.14 2009     Apr 4.48 2006     Nov 3.24 2009     May 5.27 2006     Dec 4.13 2009     Jun 3.93 2007     Jan...
How can I do regression analysis for Sales Revenue for Macys comparing it to TJX? Please...
How can I do regression analysis for Sales Revenue for Macys comparing it to TJX? Please show work and example in Excel if it's easier. Net Profit Margin 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Sales Revenue - MACYS $ 15,776,000.00 $ 22,390,000.00 $ 26,970,000.00 $ 26,313,000.00 $    24,892,000.00 $ 23,489,000.00 $ 25,003,000.00 $ 26,405,000.00 $ 27,686,000.00 $ 27,931,000.00 $ 28,105,000.00 $ 27,079,000.00 $ 25,778,000.00 $ 24,837,000.00 Net Profit Margin 2005 2006 2007...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT