A 99% confidence interval will be wider than a 95% confidence interval.

Suppose we want to get an idea of the average

return on a share in the Australian share market. If we take the returns just

on shares in the banking sector and calculate the mean return, this would be

biased as an estimate for the overall market.

The sample mean will be a more accurate

estimator if the data is more spread.

Voluntary participation is a reliable way to collect a sample to be used for estimation.

There is a theory call the Central Limit Theorem that tells us that even if the original data is not normal, the process of averaging a set of data makes the mean quite close to the normal shape, especially for larger n values (at least 30).

Imagine somehow that the population standard

deviation was known instead of having to be estimated.  Would my interval be narrower or wider?

True or False: A confidence interval will be symmetric around

the sample mean.

If I am able to get more data and my sample

doubles in size, would my interval be narrower or wider?

What proportion of this sample lives in Dili?

(Report as a percentage to 2 decimal places, e.g. 12.12%)

Construct a 95% confidence interval for the proportion of young people living in Dili.

What is the lower bound of the confidence interval?

(Report as a percentage to 2 decimal places, e.g. 12.12%)