TRW dataset ABQ_cancellations.MTW, which is on the course web site. This shows t

Question

TRW dataset ABQ_cancellations.MTW, which is on the course web site. This shows the number of scheduled and cancelled departures over 15 days at Albuquerque airport (ABQ). It is reasonable to try to model the random number of cancellations as a binomial random variable with a parameter n that varies from day to day. The issue in this question is how best to estimate the other binomial parameter, p. There are two possible estimates. One we call AvgDaily_P; it is computed by taking the mean value of the 15 daily estimates. The other we call Overall_P; it is computed by dividing the total number of cancellations by the total number of scheduled departures. Our criterion for choosing one or the other estimate is maximizing the likelihood of the data. Assuming independence across days, then the likelihood of the data is the product of the likelihoods of each of the 15 daily outcomes. But since the product of 15 probabilities will be a very small number, we usually work instead with the (natural) logarithm of the likelihood. Use Minitab to fill in all the cells marked "-9" in the worksheet. Hand in your filled-in worksheet. Then add your conclusion: which estimate does the better job on these data?

Explanation / Answer

Refer this.

http://vfu.bg/en/e-Learning/Math--Soong_Fundamentals_of_probability_and_statistics_for_engineers.pdf

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