In 100 trials of this experiment, it is expected that about 7 will result in exactly 11 flights being on time. (Round to the nearest whole number as needed.) (d) Using the binomial distribution, the probability that fewer than 11 flights are on time is 0.0377 (Round to four decimal places as needed.) Interpret the probability. In 100 trials of this experiment, it is expected that about 4 will result in fewer than 11 flights being on time. (Round to the nearest whole number as needed.) (e) Using the binomial distribution, the probability that at least 11 flights are on time is 0.9623 . (Round to four decimal places as needed.) Interpret the probability. In 100 trials of this experiment, it is expected that about 96 will result in at least 11 flights being on time. (Round to the nearest whole number as needed.) (f) Using the binomial distribution, the probability that between 9 and 11 flights, inclusive, are on time is (Round to four decimal places as needed.) (Rol.
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In the context of the binomial distribution, the probability that fewer than 11 flights are on time (0.0377) tells us that, out of 100 trials, about 4 of those trials will see fewer than 11 flights arriving as scheduled. This low probability suggests that having fewer than 11 on-time flights is quite unusual, indicating a high level of efficiency or reliability in this situation. When considering the probability that at least 11 flights are on time (0.9623), we find that it is very likely to happen—in fact, around 96 out of 100 trials will show at least this many flights arriving on time. This reinforces the idea that the flight schedule is likely to be met most of the time, making for a reassuring statistic for passengers and airline operations alike!
