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Esri EADP19-001 Exam - Topic 6 Question 24 Discussion

An ArcGIS user runs the Central Feature geoprocessing tool on a polygon feature class. The output feature is far north of the center of the feature classWhy Is the output feature off center of the feature class?
D) A weight field is not specified
A) There are more polygons In the northern part of the feature class
B) The polygons in the northern part of the feature class are larger
C) The feature class is not in the same promotion as the data frame

Esri EADP19-001 Exam - Topic 6 Question 24 Discussion

Actual exam question for Esri's EADP19-001 exam
Question #: 24
Topic #: 6
[All EADP19-001 Questions]

An ArcGIS user runs the Central Feature geoprocessing tool on a polygon feature class. The output feature is far north of the center of the feature class

Why Is the output feature off center of the feature class?

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Suggested Answer: D

by Fernanda at Mar 20, 2023, 07:39 AM

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Kristeen
10 months ago
I’ve seen this happen before, definitely check the weights if they’re not set!
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Sonia
10 months ago
Wait, is it really possible for D to be the reason? That seems odd.
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Ivory
10 months ago
C is a possibility too, but I’m not sure how that affects the output.
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Nickolas
11 months ago
I disagree, B seems more likely. Larger polygons would definitely pull the center.
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Rolland
11 months ago
I think option A makes sense. More polygons up north could shift the center.
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Dalene
11 months ago
I vaguely recall something about projection issues affecting the output, but I can't remember if that relates to option C or not.
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Destiny
11 months ago
I practiced a similar question where the feature class was off-center due to the distribution of features. I wonder if option A is the answer here?
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Olen
11 months ago
I'm not entirely sure, but I think if there’s no weight field specified, it might default to something that skews the center. That could relate to option D.
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Ty
11 months ago
I remember something about how the size and distribution of polygons can affect the central feature calculation, so maybe option B could be right?
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Raelene
11 months ago
I vaguely recall that if a weight field isn't specified, it could lead to unexpected results, so D might be worth considering as well.
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Arlene
11 months ago
I'm not entirely sure, but I feel like if the data frame and feature class aren't aligned, that could definitely throw things off, which makes C seem plausible.
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Marti
11 months ago
I think I practiced a question like this where the size of polygons mattered, so B could be a possibility too.
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Odelia
11 months ago
I remember something about how the distribution of polygons can affect the central feature, so maybe A is correct?
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Scarlet
11 months ago
Okay, let's see. We need to configure ItemA to ensure the buying rules are implemented, and the business has decided to stop buying ItemA ConfigB into Site2. I think the key here is to figure out how to control the availability of the different configurations at the different sites.
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Tawna
11 months ago
Assist, Boxer, Tunnel, or Content - this is a tough one. I'm going to have to carefully consider the details of each option to make the best guess.
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Curtis
11 months ago
Hmm, I'm a bit confused on this one. I know nmap can do OS detection, but I'm not sure if that's the specific purpose of TCP/IP stack fingerprinting. I'll have to think this through carefully.
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