ASQ Exam CQE Topic 4 Question 71 Discussion

Actual exam question for ASQ's CQE exam

Question #: 71
Topic #: 4

[All CQE Questions]

Which of the following assumptions is a robustness factor suitable for validating statistical conclusions?

ALow reliability of measures

BHigh statistical power

CLow reliability of treatment

DViolated expectations of test

Show Suggested Answer

Suggested Answer: A

by Alease at Jul 05, 2023, 11:14 PM

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Emmanuel

2 months ago

Wait, isn't low reliability of measures the opposite of what we want for robustness? I'm sticking with B) High statistical power as the best bet.

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Milly

9 days ago

Yeah, I think we should focus on high statistical power to ensure the validity of our statistical conclusions.

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Lorriane

15 days ago

Low reliability of measures can actually be a hindrance to robustness, so I think B) High statistical power is the way to go.

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Ines

1 months ago

I agree with you, high statistical power is definitely important for validating statistical conclusions.

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Jarod

2 months ago

Haha, just when you think you've got it figured out, they throw in a curveball. I'd go with B) High statistical power - can't go wrong with good old statistical rigor!

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Stefan

15 days ago

Definitely, it helps ensure the reliability and accuracy of your results.

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Dorothy

18 days ago

Yeah, it's always important to have strong statistical evidence to back up your findings.

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Mabel

20 days ago

I agree, high statistical power is crucial for validating conclusions.

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Chantell

2 months ago

Ooh, this is a tricky one. I'm leaning towards D) Violated expectations of test, because if your results defy expectations, that could indicate a more robust finding.

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Ernestine

2 months ago

I'm not sure, but I think C) Low reliability of treatment would be a red flag, not a robustness factor. That sounds like a threat to validity.

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Chi

11 hours ago

C) Low reliability of treatment could indeed be a threat to the validity of the results.

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Franchesca

5 days ago

B) High statistical power is important for detecting true effects in a study.

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Carman

8 days ago

A) Low reliability of measures can definitely impact the validity of statistical conclusions.

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Lasandra

1 months ago

D) Violated expectations of test could also indicate potential issues with the conclusions drawn.

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Lashon

1 months ago

C) Low reliability of treatment could indeed be a threat to the validity of the conclusions.

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Alyce

2 months ago

B) High statistical power is important for detecting true effects in the data.

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Fidelia

2 months ago

A) Low reliability of measures could definitely impact the validity of the statistical conclusions.

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Miesha

2 months ago

B) High statistical power seems like the most appropriate assumption for validating statistical conclusions. Robust studies need sufficient power to detect effects.

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Mitsue

2 months ago

I'm not sure about that. I think D) Violated expectations of test could also be a factor to consider.

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Latanya

2 months ago

I agree with Aliza. High statistical power helps ensure the results are reliable.

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Aliza

2 months ago

I think B) High statistical power is important for validating statistical conclusions.

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Wade

2 months ago

I'm not sure about that. I think D) Violated expectations of test could also be a factor to consider.

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Hannah

2 months ago

I agree with Loreta. High statistical power helps ensure that the results are reliable.

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Loreta

3 months ago

I think B) High statistical power is important for validating statistical conclusions.

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