# Modelling using a binomial distribution - assumptions

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#1
I've done the first part but I'm clueless when it comes to part b

Linda regularly takes a taxi to work five times a week. Over a long period of time she finds the taxi is late once a week on average. The taxi firm changes her driver and Linda thinks the taxi is late more often. In the first week with the new driver the taxi is late 3 times.
You may assume that the number of times the taxi is late in a week can be modelled with a binomial distribution.

b.One of the assumptions when modelling using a binomial distribution is that the probability of success p, in this case the probability the taxi is late, is constant throughout all the trials. Give two possible reasons why this assumption may not hold for this situation.
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1 year ago
#2
(Original post by petulantvictor)
I've done the first part but I'm clueless when it comes to part b

Linda regularly takes a taxi to work five times a week. Over a long period of time she finds the taxi is late once a week on average. The taxi firm changes her driver and Linda thinks the taxi is late more often. In the first week with the new driver the taxi is late 3 times.
You may assume that the number of times the taxi is late in a week can be modelled with a binomial distribution.

b.One of the assumptions when modelling using a binomial distribution is that the probability of success p, in this case the probability the taxi is late, is constant throughout all the trials. Give two possible reasons why this assumption may not hold for this situation.
Think about the context. What things can cause a taxi driver to have a higher/lower probablity of being late one day than the other?
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