An airline’s weekly flight data showed a 98% probability of being on time. If this airline has 15,000 flights in a year, how many flights would you predict to arrive on time? Explain whether you can use the data
to predict whether a specific flight with this airline will be on time.
thanks
.98 * 15,000 = 14,700
Only 2 percent will arrive late so your flight will probably be on time. Of course the key word is "probably" and there is no way you can tell if yours is one of the two out of one hundred that are late.
To answer this question, we need to use probability and basic mathematical calculations.
The airline's weekly flight data shows a 98% probability of being on time. This means that, on average, 98% of the flights operated by the airline are expected to arrive on time.
To predict how many flights would arrive on time in a year, we can assume that the probability remains constant throughout the year, which may not always be the case in reality.
First, let's calculate the number of flights that are expected to arrive on time in a week:
98% of 15,000 flights = (98/100) * 15,000 = 14,700 flights
Now, let's calculate the number of weeks in a year:
Since one year consists of 52 weeks, there are 52 weeks in total.
To estimate the number of flights that would arrive on time in a year, we multiply the flights per week by the number of weeks in a year:
14,700 flights/week * 52 weeks = 764,400 flights/year
Therefore, based on the given data, we can predict that approximately 764,400 flights from this airline would arrive on time in a year.
However, it's important to note that this prediction assumes a consistent probability of 98% throughout the year. Real-life circumstances, such as weather conditions or operational issues, may affect the actual on-time performance of the flights.
As for predicting whether a specific flight with this airline will be on time, we need more information. The given data only provides the probability of on-time flights for the airline as a whole. To predict whether a specific flight will be on time, we would need additional factors such as the specific flight schedule, historical data for that route, and real-time conditions.