Pressures of supply and demand act directly on the prices of airline tickets. As the seats available on the plane begin to fill,
airlines raise the price. If seats on a flight do not sell well, an airline may discount the tickets or even cancel the flight. Allie Henrich, a BYU-Idaho student, WANTED TO PREDICT THE PRICE OF TICKETS 14 DAYS BEFORE A FLIGHT BASED ON THE PRICE OF TICKETS LISTED 90 DAYS BEFORE THE SAME FLIGHT. For her study she compared the prices of one-way flights from London's Heathrow Airport to various destinations in Europe. Using Travelocity.com, she recorded the lowest published fares for 90 nonstop midweek flights 90 days in advance and then found the lowest published price for the same destination again 14 days in advance. The prices (in US dollars) are given in the file DirectFlightCosts. Notice that for some destinations, flights were not available. 1. Compute the sample correlation coefficient of the 14 Days before flight ticket prices compared with the 90-Days before flight ticket prices. Give your answer accurate to three decimals.2. Create a scatterplot using these two variables. Using this scatterplot and referring to the correlation coefficient above, select the answer that best describes the data illustrated in the scatterplot.a. Linear with a fairly strong negative associationb. Linear with a fairly strong positive associationc. Linear with a strong negative associationd. Nonlinear
What you can do in this case is a rule of three to determine the length of each bow. We have then: 1/4 ---> 2 x ------> 1 Clearing x we have: x = (1/2) * (1/4) x = 1/8 Answer: the length of ribbon in each bow is x = 1/8 Equivalently: x = (1/4) / 2 Option 3
