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APICS Exam CPIM-MPR Topic 4 Question 75 Discussion

Actual exam question for APICS's CPIM-MPR exam
Question #: 75
Topic #: 4
[All CPIM-MPR Questions]

When quantitative data are being evaluated, a very small bias in a forecast can best be explained by which of the following statements?

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Suggested Answer: B

Contribute your Thoughts:

Christiane
17 days ago
Well, at least it's not a trick question like 'when does a bear sit in the woods?' Haha, gotta love these statistics problems.
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Rolf
23 days ago
Hmm, I'm going with C. The skewed variability of the forecast data must be the culprit. That's my best guess!
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Adelle
2 days ago
User 1: I think it's A. Positive forecast errors offset negative ones.
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Kaitlyn
1 months ago
B. is my pick. If all the forecast errors were about the same size, that could lead to a small overall bias, right?
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Norah
20 days ago
C) The variability of forecast data was skewed.
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Madonna
21 days ago
B) The absolute values of all forecast errors were approximately equal.
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Derrick
28 days ago
A) Positive forecast errors approximately offset negative forecast errors.
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Hollis
1 months ago
D. using a small alpha factor makes the most sense to me. Doesn't that help reduce bias in the forecasting model?
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Kaycee
2 days ago
True, having all forecast errors with approximately equal absolute values can also explain a small bias.
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Mitzie
10 days ago
The variability of forecast data being skewed could also contribute to a small bias.
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Tamie
24 days ago
I think positive forecast errors offsetting negative forecast errors is also a good explanation.
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Fernanda
1 months ago
Yes, using a small alpha factor can help reduce bias in the forecast.
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Jennifer
2 months ago
I think the correct answer is A. Positive and negative forecast errors offsetting each other seems like the most logical explanation for a small bias.
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Arletta
14 days ago
I think it could also be because a very small alpha factor was used.
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Myrtie
21 days ago
I agree, positive and negative errors balancing out makes sense.
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Heike
2 months ago
But if positive forecast errors offset negative ones, it would explain the small bias.
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Leatha
2 months ago
I disagree, I believe it's C.
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Heike
2 months ago
I think the answer is A.
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