If I had a nickel for every time I saw 'sequential random sampling' on an exam, I'd have... well, a nickel. But hey, at least it's better than 'random sequential sampling', am I right?
I'm more of a 'go big or go home' kind of guy, so I'm picking B and D. Simple random sampling with replacement and sequential random sampling with replacement? That's living on the edge, baby!
I'm going with A and C. Stratified random sampling is a great way to ensure we get a representative sample, and simple random sampling without replacement is a classic.
Woah, hold up! Simple random sampling with replacement? Isn't that just putting the data back in the hat and pulling it out again? Seems a bit like cheating to me.
A and C seem like the way to go. Simple random sampling without replacement and stratified random sampling without replacement are both good options for model assessment.
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