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IASSC ICBB Exam - Topic 1 Question 63 Discussion

Actual exam question for IASSC's ICBB exam
Question #: 63
Topic #: 1
[All ICBB Questions]

What conclusion is most correct about the Experimental Design shown here with the response in the far right column?

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Suggested Answer: C

by Jennie at Apr 09, 2024, 01:19 PM

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Luis
3 months ago
B is interesting, but I don’t see how they can be the only ones affecting it.
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Lucina
4 months ago
E makes sense too, not enough runs to draw solid conclusions.
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Jesusa
4 months ago
Wait, are we sure about that? I thought Adv had a strong impact.
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Alesia
4 months ago
Totally agree, A seems spot on!
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Catalina
4 months ago
Looks like no factors hit that 95% mark.
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Irene
5 months ago
I vaguely remember that if there aren't enough experimental runs, we can't draw strong conclusions. So, option E might be a valid point to consider.
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Loreta
5 months ago
I'm a bit uncertain about whether the response rate really increases with Adv. It seems logical, but I need to double-check the data from our practice problems.
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Ashley
5 months ago
I think I saw a similar question where we had to identify which factors were significant. I feel like Adv and Bev might be the key ones here, but I can't recall the exact details.
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Ellen
5 months ago
I remember we discussed how a 95% confidence level is crucial for determining significance, but I'm not sure if all factors meet that threshold here.
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Alona
5 months ago
Hmm, this is a tricky one. I'm not entirely sure how to interpret the lack of p-values in the output. I may need to make some assumptions or inferences to arrive at the best conclusion.
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Delsie
5 months ago
Based on the information provided, I think option B is the most correct. The output shows that Constant, Adv, and Bev are the only factors with effects greater than 95% confidence.
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Deeanna
5 months ago
I'm a bit confused by the lack of p-values in the output. Without those, it's going to be tough to determine statistical significance. I'll need to double-check the experimental design to see if there are any clues there.
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Jacquelyne
5 months ago
Okay, let me think this through step-by-step. The question is asking about the conclusions we can draw from the experimental design, so I'll need to focus on interpreting the results shown in the output.
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Irving
5 months ago
Hmm, this looks like a tricky one. I'll need to carefully review the MINITAB output and the experimental design to determine which factors are statistically significant.
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Aaron
5 months ago
I've seen this type of question before. I think the best approach is to start by creating the storage account, and then work on the managed identity piece. That should get me on the right track.
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Amie
5 months ago
Ah, I remember learning about this in class. Ultrasonic humidifiers use high-frequency vibrations to turn water into a fine mist. That's the key feature that sets them apart from the other types. I'm confident that's the right answer.
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Aileen
5 months ago
Okay, if I recall right, ROI is net profit divided by investment cost. But I can't shake off the feeling that "10%" is too low given the context.
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Phyliss
10 months ago
Wow, this experiment must have been sponsored by the 'Ministry of Silly Designs'! I hope they have a backup plan for when the results turn out to be a total mess.
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Ammie
9 months ago
User 3: Yeah, it seems like the other options are not supported by the experimental design.
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Tina
9 months ago
User 2: I agree, Constant, Adv and Bev are the only factors statistically affecting the response rate with 95% confidence or more.
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Zana
9 months ago
User 1: I think option B is the most correct conclusion.
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Audra
10 months ago
Wait, where's the control group? This whole thing looks a bit sketchy to me. I'm going to have to go with A on this one.
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Brittni
9 months ago
I see your point, but I still think A is the best choice. No factor has enough statistical confidence to impact the response rate.
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Junita
9 months ago
I disagree, I believe D is the most accurate conclusion. The response rate only needs Adv and Bev factors set at the low level.
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Myong
10 months ago
I think B is the correct conclusion here. Constant, Adv, and Bev are the only factors affecting the response rate.
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Brandon
10 months ago
Haha, this design is a real head-scratcher! I guess the experimenters got a little carried away with the 'high' and 'low' levels. E seems like the safest bet here.
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Suzan
9 months ago
User 3: It does seem like there's not enough data to draw any solid conclusions.
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Shenika
9 months ago
User 2: I agree, maybe E is the safest option to go with.
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Theola
10 months ago
User 1: Yeah, this design is definitely confusing.
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Raul
11 months ago
I'm not sure about this one. The design seems a bit incomplete, but I would go with D. Minimizing the factors seems like the best way to get the largest response.
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Pilar
9 months ago
I agree with you. D seems like the most logical conclusion based on the experimental design.
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Cassi
9 months ago
I see your point, but I still believe D is the most accurate. Keeping Adv and Bev at low levels for the largest response.
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Lucy
10 months ago
But what about C? Increasing Adv leads to an increase in the response rate.
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Ahmad
10 months ago
I think B is the correct conclusion. Constant, Adv, and Bev are the only factors affecting the response rate.
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Dortha
11 months ago
I think the correct answer is B. The output clearly shows that Adv and Bev are the only factors with statistical significance at the 95% level.
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Stefany
10 months ago
It's clear that the other factors do not have enough statistical confidence to affect the response rate.
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Phuong
10 months ago
I agree, the data supports that only Adv and Bev have a significant impact on the response rate.
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Catina
11 months ago
But what about the lack of P-values in the MINITABTM output? Doesn't that mean we can't conclude anything?
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Nickie
11 months ago
I disagree, I believe the correct conclusion is D) The response level is statistically concluded to only need the Adv and Bev factors set at the low level to get the largest response rate.
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Catina
11 months ago
I think the correct conclusion is B) Constant, Adv and Bev are the only factors statistically affecting the response rate with 95% confidence or more.
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