Respuesta :
It isn't appropriate for the consumer group to perform a hypothesis test for the mean payout of all customers.
The major reason is because the sample is short and it is given that most consumer has zero payouts.
What do we know?
- Most customers have zero payouts and a few have substantial payouts
- Sample size = 18
- Sample mean = $579.80
- Sample variance = $751.30
How to know if it is appropriate to perform hypothesis testing?
The size of the sample taken is not enough large. When sample isn't large enough, it represents skewed information of the population.
The population itself contains many customers who have zero payouts, thus the population isn't normally distributed for insurance claim.
Because of these reasons, the sample mean won't help in deducing conclusions about population mean.
Thus, it is inappropriate for the consumer group to perform a hypothesis test for the mean payout of all customers.
Learn more about population mean estimation here:
https://brainly.com/question/20747890
It is not appropriate to perform a hypothesis test for the mean payout of all customers, mostly because the sample is really small.
What do we know?
- Most customers have zero payouts and a few have substantial payouts
- Sample size = 18
- Sample mean = $579.80
- Sample variance = $751.30
What does this imply?
The first thing you can see is the sample size, it seems to be really small for a company with thousands of customers, is really probably that just 18 of them do not represent accurately the whole population.
We also do know that a large proportion of the population has zero payouts, so the population is skewed.
Just because of these two motives, the mean of the sample most likely does not accurately portray the whole population, thus is not appropriate for the consumer group to perform a hypothesis test for the mean payout of all customers.
If you want to know more about samples and populations, you can read:
https://brainly.com/question/13880665
