91影视

We need to explain whether it might be difficult to give the survey to an $\mathrm{SRS}$of fans.

Simple random sampling uses a sample of size $\mathrm{n}$in which every sample of size $\mathrm{n}$has an equal chance of being chosen.

It is not practical to get a simple random sample $\left(\mathrm{SRS}\right)$from the fans, because we would need to randomly select $10\%$of the seats and then find every person who was seated in that seat, which will be very time-consuming.

Moreover, we would then still need to take the survey from each of these people, once the people were found.

We need to explain whether it would be better to select a stratified random sample using the lettered rows rather than the numbered sections as strata.

Stratified random sampling draws simple random samples from independent subgroups (stratum).

we using the lettered rows as strata will be better than using the numbered sections as strata because the numbered sections are all similar when the lettered rows as not similar, so the seats near the court cost the most, while the seats in the top row cost the least.

If we would then use the lettered rows as strata, then this would allow us to compare the opinion of the fans to the cost of their ticket and thus we are able to take into account the effect the cost of the ticket has on the opinion.

We need to explain how to select a cluster sample of fans. What is the benefit of using a cluster sample in this context.

Cluster sampling divides the population into non-overlapping subgroups and some of these subgroups are then in the samples.

The $50$numbered sections are nonoverlapping subgroups, which are also similar.

If we randomly select $5\mathrm{to}50$numbered sections, then we have randomly selected $10\%$of the numbered sections and thus we selected $10\%$of the fans.

A possible cluster sample then contains all individuals in $5$randomly selected number sections.