Table 11.3.2 shows the on-time performance of nine airlines, both for one month (May 2010) and for the preceding four (January to April 2010). These numbers represent percentages of flights that arrived on time. We will investigate the consistency of performance by examining the relationship, if any, between the one month and the preceding four.
a. Draw a scatterplot of this data set and comment on the relationship.
b. Find the correlation between performance for one month and for the preceding four. Is there a strong relationship?
c. Find the coefficient of determination and say what it represents.
d. Find the linear regression equation to predict the performance for May from that of the previous four months.
e. Find the predicted value and residual value for American Airlines. Say what each one represents.
f. Find the standard error of estimate. What does this measure?
g. Find the standard error of the regression coefficient.
h. Find the 95% confidence interval for the regression coefficient.
i. Test at the 5% level to see whether or not there is a significant relationship between performance during these two time periods. What does this tell you about consistency in airline performance?

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TABLE 11.3.2 Airline On-Time Performance Ailine Alaska American Continental Delta Frontier JetBlue Southwest United US Airways January Ari 87.58% 78.18 8032 80.34 81.54 75.12 81.21 83.98 81.16 May 91.50% 76.58 82.48 75.64 80.20 82.70 80.35 84.77 85.29