Statistics 110 module 5 problem set portage learning

1. why do we collect samples?: to collect data from populations to make
inferences and answer questions about a population of interest 2. element: the
entity for which data are collected
3. population: the collection of al the elements of interest
4. sample: a subset of the population
5. simple random sampling of size n from a population of size N: a sample
selected such that each possible sample of size n has the same probability of
occurring
6. point estimation: a form of statistical inference in which we use data from a
sample to compute a value of a sample statistic that serves as an estimate of a
population parameter
7. sampling distribution of x-bar: the probability distribution of a possible values
of the sample mean x-bar
8. expected value of sample mean: population mean
9. central limit theorem: in selecting random samples of size n from a
population, the sampling distribution of the sample mean x-bar can be
approximated by a normal distribution as the sample size becomes large
10. sample proportion p-bar: the point estimate of the population proportion p
11. sampling distribution of p-bar: the probability distribution of all possible
values of the sample proportion p-bar