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Fractional Factorial designs are used to reduce the ____________ because the number of runs has been lowered.
Suggested Answer: A
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38 comments · newest first
MI
Mike
11 months ago
I thought it was about data points, not just cost.
KA
Kate
11 months ago
A makes the most sense, less runs means less expense!
TY
Tyra
11 months ago
Wait, are we sure it's not B? Seems like people matter too.
ST
Stephen
12 months ago
I agree, A is the right choice!
VO
Vonda
12 months ago
Definitely A! It cuts down on time and cost.
CA
Carri
12 months ago
I feel like it could be about the number of data measurement points too, but I can't recall any specific examples. A seems more likely though.
PA
Paris
1 year ago
I practiced a question like this before, and I believe it was about minimizing costs and time. So, I would lean towards A as well.
ME
Melissa
1 year ago
I'm not entirely sure, but I remember something about how they help with the number of runs needed. Maybe it's related to option A?
AL
Alecia
1 year ago
I think fractional factorial designs are mainly about reducing the time and cost of experiments, right? That sounds familiar.
DO
Doyle
1 year ago
I'm pretty confident that the answer is A - time and cost of experiments. Fractional factorial designs are all about reducing the number of experimental runs, which in turn reduces the overall time and cost.
ST
Stephanie
1 year ago
I'm a bit confused here. Is it the number of people involved, the number of data measurement points, or the output summary that is reduced in fractional factorial designs? I'll have to think this through carefully.
CH
Chantell
1 year ago
Hmm, this seems straightforward. Fractional factorial designs are used to reduce the time and cost of experiments, since the number of runs is lowered.
LO
Loren
1 year ago
Okay, I've got it. Fractional factorial designs are used to reduce the time and cost of experiments, since the number of runs has been lowered. That's the key point here.
LO
Long
1 year ago
State Machine seems like the most logical choice here for handling UI navigation and data processing. I'm pretty confident in that.
LO
Lorrie
1 year ago
Wait, does this mean I can run my experiments faster and spend less money? Sign me up for that!
LA
Lamonica
1 year ago
Output summary? Really? I think you're way off base on this one, my friend. Clearly, it's the time and cost savings that matter most.
LO
Lorenza
1 year ago
A) Time and cost of experiments
WI
William
1 year ago
C) Number of data measurement points
YU
Yun
1 year ago
A) Time and cost of experiments
GR
Gracia
1 year ago
Fewer people involved? I don't think that's the main advantage here. It's all about optimizing the experimental setup.
PE
Pearlene
1 year ago
I agree, the main advantage of Fractional Factorial designs is to reduce the number of data measurement points.
LI
Lina
1 year ago
C) Number of data measurement points
BR
Brock
1 year ago
A) Time and cost of experiments
JO
Joaquin
2 years ago
Hmm, I'd say it's the number of data measurement points that gets reduced. Gotta love those efficient experimental designs!
CA
Catina
1 year ago
D) Output summary
DA
Dalene
1 year ago
Absolutely, Fractional Factorial designs are great for reducing the number of data points.
LE
Lezlie
1 year ago
C) Number of data measurement points
TH
Thea
1 year ago
A) Time and cost of experiments
PA
Paris
2 years ago
Fractional factorial designs definitely help cut down on time and cost of experiments. A no-brainer for me!
LE
Levi
1 year ago
Yes, it simplifies the process without sacrificing accuracy.
DE
Detra
1 year ago
C) Number of data measurement points
CH
Cherry
1 year ago
I agree, it's a great way to save resources.
CA
Casandra
1 year ago
A) Time and cost of experiments
PE
Peggie
1 year ago
C) Number of data measurement points
CA
Cathrine
1 year ago
A) Time and cost of experiments
BU
Buck
2 years ago
C) Number of data measurement points. With fewer runs, we need to be strategic about where we collect data.
ST
Stephaine
2 years ago
I agree with Lorean, using Fractional Factorial designs can save time and money.
LO
Lorean
2 years ago
A) Time and cost of experiments