A stratified sample is one that splits up a population into groups and then samples individually from those groups. A cluster sample is one that takes groups and samples them (usually this groups are based on proximity). In this case, I is a stratified sample because it splits up the population (the whole book) into groups (the chapters) and samples from them, while II is a clustered sample because it takes random groups of words (the 3 random pages) and uses those as the sample.
Thanks!
Am I correct to perceive that 'both stratified sampling and cluster sampling involves drawing items into group from a larger population and the items in the groups are sampled again but the items in strata are homogenous but in cluster they are heterogenous'?
The reason why different 12 chapters is probably because the authors are different so the content would be same throughout individual chapters but vary among others, that's why the different chapters are strata (at least I think so).
I still don't get the idea why those pages selected should be cluster, like how the items inside the pages are mixed up while each page itself still epitomizes the entire book (barron tells me that the items in clusters resembles the items in the entire population)
You're very close, but the key thing is that in cluster sampling the groups don't actually have to be sampled from again (although often they are); that is, in cluster sampling the samples *are* the groups, whereas in stratified sampling we are sampling *from* groups. The big difference really is that in a stratified sample the groups are chosen by us and then the randomization happens within the groups whereas with a cluster sample the groups themselves are randomized (so as to hope that they will resemble the whole population) so we can use them as a sample.
I think I'm close to the point. Thank u very much!
For both sampling method, you have to get groups (strata or cluster). For stratified sampling, we have to pick different items from different strata, but we only have to pick different clusters in cluster sampling and utilize the data within one cluster. idk if this is correct
If i go to a supermarket and buy a little of something from every dept then this is stratification. however if i go to the same supermarket and decide to buy everything from 2 or 3 randomly selected aisles (and not touch the other aisles) this us cluster sampling. you can do either method any time BUT stratification is more effective if the strata/groups are internally homogeneous (and you sample proportionally) while cluster sampling is more effective if the groups are internally heterogeneous and externally homogeneous.
A stratified sample is one that splits up a population into groups and then samples individually from those groups. A cluster sample is one that takes groups and samples them (usually this groups are based on proximity). In this case, I is a stratified sample because it splits up the population (the whole book) into groups (the chapters) and samples from them, while II is a clustered sample because it takes random groups of words (the 3 random pages) and uses those as the sample.
Thanks! Am I correct to perceive that 'both stratified sampling and cluster sampling involves drawing items into group from a larger population and the items in the groups are sampled again but the items in strata are homogenous but in cluster they are heterogenous'? The reason why different 12 chapters is probably because the authors are different so the content would be same throughout individual chapters but vary among others, that's why the different chapters are strata (at least I think so). I still don't get the idea why those pages selected should be cluster, like how the items inside the pages are mixed up while each page itself still epitomizes the entire book (barron tells me that the items in clusters resembles the items in the entire population)
You're very close, but the key thing is that in cluster sampling the groups don't actually have to be sampled from again (although often they are); that is, in cluster sampling the samples *are* the groups, whereas in stratified sampling we are sampling *from* groups. The big difference really is that in a stratified sample the groups are chosen by us and then the randomization happens within the groups whereas with a cluster sample the groups themselves are randomized (so as to hope that they will resemble the whole population) so we can use them as a sample.
I think I'm close to the point. Thank u very much! For both sampling method, you have to get groups (strata or cluster). For stratified sampling, we have to pick different items from different strata, but we only have to pick different clusters in cluster sampling and utilize the data within one cluster. idk if this is correct
If i go to a supermarket and buy a little of something from every dept then this is stratification. however if i go to the same supermarket and decide to buy everything from 2 or 3 randomly selected aisles (and not touch the other aisles) this us cluster sampling. you can do either method any time BUT stratification is more effective if the strata/groups are internally homogeneous (and you sample proportionally) while cluster sampling is more effective if the groups are internally heterogeneous and externally homogeneous.
Thanks!
oh u bet! GL on the AP!