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Worldatwork C3E Exam - Topic 2 Question 5 Discussion

How can compensation professionals ensure their statistical data are not distorted?
B) Develop a plan that provides an objective approach to collecting, organizing and displaying data
A) Use statistical software, which prevents distortion of data.
C) Avoid training that shows how data can be distorted, as that training might cause one to distort data subconsciously.
D) Distortion of data is commonly accepted as a method for making compelling arguments for change in orgs.

Worldatwork C3E Exam - Topic 2 Question 5 Discussion

Actual exam question for Worldatwork's C3E exam
Question #: 5
Topic #: 2
[All C3E Questions]

How can compensation professionals ensure their statistical data are not distorted?

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Suggested Answer: B

by Leatha at May 09, 2022, 08:15 AM

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Sanjuana
10 months ago
Not sure about that last option, seems unethical.
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Lanie
10 months ago
Distortion for arguments? That's just wrong!
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Hoa
11 months ago
Wait, avoiding training? That sounds risky...
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Janna
11 months ago
I totally agree, a solid plan is key!
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Carisa
11 months ago
Using statistical software is a must!
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Jacquelyne
11 months ago
I recall that distortion can sometimes be used strategically, but I don't think it's ethical. Option D seems really problematic to me.
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Eva
11 months ago
I feel like we covered a question similar to this before, and I think avoiding bias in training is crucial. Option C sounds a bit off to me, though.
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Salena
11 months ago
I'm not entirely sure, but I think using statistical software can help minimize errors. However, I wonder if it’s enough on its own.
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Tawna
11 months ago
I remember discussing the importance of having a structured plan for data collection in class. It seems like option B might be the right approach.
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Cory
11 months ago
The Analyze Image operation in the Computer Vision service sounds like the way to go. It can probably detect both the faces and the sunglasses, which is exactly what we need for this task.
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Dustin
12 months ago
I'm pretty confident on this one. The champion model is Candidate 2 because the area under its curve is larger, which means it has better overall predictive performance.
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Maile
12 months ago
I recall something about Paramiko, but did we cover a specific library built on it? I feel like I've seen similar terms before…
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