Analysis of Cost Behavior for JetBlue Airways JetBlue Airways is a major American low cost airline, and the seventh largest airline in the United States by passengers carried and has headquarters in Long Island, New York. They have a fleet of 262 aircraft, and offer flight amenities from their "Core" experience which includes unliminated brand-namd snacks and soft drinks, to their "Mint" experience, which inludes tapas-style dining, lie-flat seating, complimentary pre-departure drink with premium spirits, etc. This is from their JetBlue fact sheet. Anyway, here is the case! Please open the 2019 and 2014 10-ks for JetBlue; both are posted in the same Canvas folder as this case. On both 10-k's, please refer to "Item 6," "Selected Financial Data." I have inserted a data table in the "Data&BreakEven" worksheet. Please complete the data table first. 1. Prepare a simple regression of Operating Expenses as a function of Revenue passengers carried. Prepare a plot of the regression results. Include in your XY scattergram a trendline, R, and regression formula. Be sure the regression formula is not in scientific notation. Please note that JetBlue shows Operating expenses in Smillions and revenue passengers in thousands. I suggest, for ease of interpretation, that you convert one of the two amounts such that they are stated in the same demonimation. For example, JetBlue reports 2019 Operating expenses as $7,294 million. I converted operating expenses for my analysis to thousands, with the amount after conversion being $7,294,000 thousand. Be sure your regression line exactly intersects the axis (either Yor which ever it may be). 2. Prepare a simple regression of Operating revenues as a function of Revenue passengers carried. Prepare a plot of the regression results. Include in your XY scattergram a trendline, R, and regression formula. Be sure the regression formula is not in scientific notation. Please note that Operating revenues is shown in Smillions. I suggest, for ease of interpretation, making the same adjustment to Revenue passengers as I recommend in #1. Be sure your regression line exactly intersects the axis (either Yor which ever it may be). 3. Prepare a simple regression of Operating expenses as a function of average number of departures. D Prepare a plot of the regression results. Include in your XY scattergram a trendline, R?, and regression formula. Be sure the regression formula is not in scientific notation. Again please note that Departures are the actual number, they are not summarized in thousands or millions. In other words, I recommend restating Departures into thousands, for example I restated 2019 Departures of 368,355 to 369. " 5. Using the regression equations derived in #1 and #2, estimate the number of Revenue passengers to be carried for JetBlue to break even. Subtract the Operating expense equation from the Operating revenues equation, plugging in Revenue passengers carried until the result is $0. That will be your break-even point, on average, over the years 2010 - 2019? 6. I am sure you noticed the negative intercepts in two of your regression equations? This can be explained through a concept referred to as the "relevant range" in a regression formula. Would you please explain the regression intercepts using the "relevant range" definition? 1 2 3 4 5 6 7 8 9 Departures (thousands) 368 366 JetBlue Airways Revenue Operating Operating passengers revenues expenses carried (thousands) (thousands) (thousands) $8,094,000 $7,294,000 42,728 7,658,000 7,392,000 42,150 7,012,000 6,039,000 40,038 6,584,000 5,324,000 38,263 6,416,000 5,200,000 35,101 5,817,000 5,302,000 32,078 5,441,000 5,013,000 30,463 4,982,000 4,606,000 28,956 4,504,000 4,182,000 26,370 3,779,000 3,446,000 24,254 353 Year 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 10 11 12 13 14 15 16 17 18 337 316 294 282 264 243 225 Analysis of Cost Behavior for JetBlue Airways JetBlue Airways is a major American low cost airline, and the seventh largest airline in the United States by passengers carried and has headquarters in Long Island, New York. They have a fleet of 262 aircraft, and offer flight amenities from their "Core" experience which includes unliminated brand-namd snacks and soft drinks, to their "Mint" experience, which inludes tapas-style dining, lie-flat seating, complimentary pre-departure drink with premium spirits, etc. This is from their JetBlue fact sheet. Anyway, here is the case! Please open the 2019 and 2014 10-ks for JetBlue; both are posted in the same Canvas folder as this case. On both 10-k's, please refer to "Item 6," "Selected Financial Data." I have inserted a data table in the "Data&BreakEven" worksheet. Please complete the data table first. 1. Prepare a simple regression of Operating Expenses as a function of Revenue passengers carried. Prepare a plot of the regression results. Include in your XY scattergram a trendline, R, and regression formula. Be sure the regression formula is not in scientific notation. Please note that JetBlue shows Operating expenses in Smillions and revenue passengers in thousands. I suggest, for ease of interpretation, that you convert one of the two amounts such that they are stated in the same demonimation. For example, JetBlue reports 2019 Operating expenses as $7,294 million. I converted operating expenses for my analysis to thousands, with the amount after conversion being $7,294,000 thousand. Be sure your regression line exactly intersects the axis (either Yor which ever it may be). 2. Prepare a simple regression of Operating revenues as a function of Revenue passengers carried. Prepare a plot of the regression results. Include in your XY scattergram a trendline, R, and regression formula. Be sure the regression formula is not in scientific notation. Please note that Operating revenues is shown in Smillions. I suggest, for ease of interpretation, making the same adjustment to Revenue passengers as I recommend in #1. Be sure your regression line exactly intersects the axis (either Yor which ever it may be). 3. Prepare a simple regression of Operating expenses as a function of average number of departures. D Prepare a plot of the regression results. Include in your XY scattergram a trendline, R?, and regression formula. Be sure the regression formula is not in scientific notation. Again please note that Departures are the actual number, they are not summarized in thousands or millions. In other words, I recommend restating Departures into thousands, for example I restated 2019 Departures of 368,355 to 369. " 5. Using the regression equations derived in #1 and #2, estimate the number of Revenue passengers to be carried for JetBlue to break even. Subtract the Operating expense equation from the Operating revenues equation, plugging in Revenue passengers carried until the result is $0. That will be your break-even point, on average, over the years 2010 - 2019? 6. I am sure you noticed the negative intercepts in two of your regression equations? This can be explained through a concept referred to as the "relevant range" in a regression formula. Would you please explain the regression intercepts using the "relevant range" definition? 1 2 3 4 5 6 7 8 9 Departures (thousands) 368 366 JetBlue Airways Revenue Operating Operating passengers revenues expenses carried (thousands) (thousands) (thousands) $8,094,000 $7,294,000 42,728 7,658,000 7,392,000 42,150 7,012,000 6,039,000 40,038 6,584,000 5,324,000 38,263 6,416,000 5,200,000 35,101 5,817,000 5,302,000 32,078 5,441,000 5,013,000 30,463 4,982,000 4,606,000 28,956 4,504,000 4,182,000 26,370 3,779,000 3,446,000 24,254 353 Year 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 10 11 12 13 14 15 16 17 18 337 316 294 282 264 243 225