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In partitioning data for model assessment, which sampling methods are acceptable? (Choose two.)
Suggested Answer: D
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40 comments · newest first
WI
Winifred
11 months ago
I thought sampling with replacement was always okay?
LY
Lynelle
11 months ago
Totally agree, A and C are solid methods!
EV
Evette
11 months ago
Wait, is D really a thing? Sounds off.
TA
Tamra
12 months ago
I think B could work too, but not as well.
KA
Kaycee
12 months ago
A and C are the best choices!
KA
Kati
1 year ago
I’m leaning towards A and C too, but I remember something about replacement being tricky in model assessment.
AN
Anabel
1 year ago
I practiced a question like this, and I feel like both A and C are the right choices, but I’m a bit confused about the replacement part.
NE
Nell
1 year ago
I think stratified random sampling without replacement is definitely one of the acceptable methods, but I can't recall if the other one is simple random sampling with or without replacement.
MO
Mollie
1 year ago
I remember that simple random sampling without replacement is often used, but I'm not sure about the second option.
MI
Mitsue
1 year ago
I'm a bit confused on the difference between simple random sampling with and without replacement. I think without replacement is the way to go, but I'm not 100% sure about the other option. I'll have to review my notes before answering this one.
LA
Lashawnda
1 year ago
Okay, let me think this through. Simple random sampling without replacement makes sense since we want to avoid duplicates in the training and test sets. And stratified random sampling is also a good choice to ensure the distributions are representative. I'll go with those two.
HO
Horace
1 year ago
Hmm, I'm a bit unsure about this one. I know simple random sampling is acceptable, but I can't remember if with or without replacement is the right approach. And I'm not confident about the other option.
CU
Curtis
1 year ago
I'm pretty sure simple random sampling without replacement and stratified random sampling without replacement are the two correct options here. Those are the standard methods we've learned for partitioning data.
RI
Rikki
1 year ago
The key here is to focus on the question and what it's asking for. Since it's asking about influential observations, I think the Cook's D by Observation plot is the way to go.
GR
Gracie
1 year ago
Hmm, I'm a bit unsure about this one. I know IPSec provides secure network communication, but I'm not sure which of these options would work best with it for accessing files on a NAS. I'll have to think this through carefully.
BE
Bernardo
1 year ago
I'm a little confused by the wording of this question. It doesn't seem to match up perfectly with the answer choices provided. I'll have to re-read it a few times to make sure I understand what they're asking for.
MA
Marya
1 year ago
Has to be B, right? I recall it's about categorizing inventory based on quantity needed.
RE
Renea
1 year ago
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?
AR
Arlene
1 year ago
B) Simple random sampling with replacement
SH
Sheron
1 year ago
I agree, 'sequential random sampling' does sound better than 'random sequential sampling'.
MO
Monte
1 year ago
C) Stratified random sampling without replacement
LI
Ling
1 year ago
A) Simple random sampling without replacement
LE
Lettie
1 year ago
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!
CA
Carmen
1 year ago
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.
FR
France
1 year ago
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.
NE
Nell
1 year ago
I think it's important to choose the right sampling method for accurate model assessment.
BO
Bo
1 year ago
D) Sequential random sampling with replacement
TW
Twanna
1 year ago
B) Simple random sampling with replacement
PA
Paris
1 year ago
Yeah, I agree. Sampling with replacement does seem a bit like cheating.
GA
Gabriele
1 year ago
C) Stratified random sampling without replacement
LI
Lilli
1 year ago
C) Stratified random sampling without replacement
JA
Jaime
1 year ago
A) Simple random sampling without replacement
LO
Loren
1 year ago
A) Simple random sampling without replacement
HO
Hoa
2 years ago
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.
MA
Maryanne
1 year ago
Those are the two acceptable sampling methods for partitioning data for model assessment.
RA
Raul
1 year ago
C) Stratified random sampling without replacement
JI
Jill
1 year ago
A) Simple random sampling without replacement
JU
Julian
2 years ago
I'm not sure about D, but I know A and C are commonly used for sampling.
CA
Carmela
2 years ago
I agree with Sheldon. A and C make sense for model assessment.
SH
Sheldon
2 years ago
I think A and C are acceptable.