Question

http://prntscr.com/3g1wlr

Answer 1

what do you think?

Answer 2

look over the info I sent you

Answer 3

d

Answer 4

and why?

Answer 5

think again

Answer 6

I believe the answer is c.
When we know something about a population, how it is composed, and if such a composition has a relevant meaning to our study, we may stratify our population. We stratify by dividing the population into a number of non-overlapping sub-groups, or strata. Then we choose a separate SRS in each strata and combine these SRSs to form a sample. For example, a population of school districts in the state of New Jersey can be divided into urban and suburban districts. The goal is to have as much homogeneity in each strata as possible.

Answer 7

this is the definition of stratified random

Answer 8

Stratified sampling is commonly used probability method that is superior to random sampling because it reduces sampling error. A stratum is a subset of the population that share at least one common characteristic. Examples of stratums might be males and females, or managers and non-managers. The researcher first identifies the relevant stratums and their actual representation in the population. Random sampling is then used to select a sufficient number of subjects from each stratum. "Sufficient" refers to a sample size large enough for us to be reasonably confident that the stratum represents the population. Stratified sampling is often used when one or more of the stratums in the population have a low incidence relative to the other stratums.

Answer 9

exactly Miracrown

Answer 10

so this would mean dividing the population into strata of age

Answer 11

and would give a non bias representation of opinions

Answer 12

Yes, that is the basic idea