In this lesson, we will use a scatterplot and a regression line to solve the following problem.
The Problem |
The Table 1 below lists the estimated numbers in millions of airline passengers at some of the fastest growing airports in 1992 and 2005. (Source: Federal Aviation Administration.) Raleigh-Durham International had 4.9 million passengers in 1992. Assuming Raleigh-Durham International follows the same trend in growth as the other airports reported in Table 1 below, estimate the number of passengers it may have in 2005. Compare this result with the Federal Aviation Administration estimation of 10.3 million passengers. |
TABLE 1 Airline Passengers (in millions) | ||
AIRPORT |
1992 | 2005 |
Harrisburg International | 0.7 | 1.4 |
Dayton International | 1.1 | 2.4 |
Austin Robert Mueller | 2.2 | 4.7 |
Milwaukee General Mitchell | 2.2 | 4.4 |
Sacramento Metropolitan | 2.6 | 5.0 |
Fort Lauderdale-Hollywood | 4.1 | 8.1 |
Washington Dulles | 5.3 | 10.9 |
Greater Cinninnati | 5.8 | 12.3 |
In order to solve this problem, we will:
a). Make a scatterplot of the data using the 1992 data for X-values and the corresponding 2005 data for Y-values. Predict whether the correlation coefficient will be positive or negative.
b). Find the least-squares regression line.
Then the results will be used to make the estimate of the number of passengers in 2005 for the Raleigh-Durham International Airport.
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