Esri Exam EADP19-001 Topic 10 Question 36 Discussion

Actual exam question for Esri's EADP19-001 exam

Question #: 36
Topic #: 10

An ArcGlS user has a point feature class and needs to determine whether there are any spatial outliers. For this project, a spatial outlier is defined as any feature that is greater than one standard deviation from the mean center of the features.

Which Spatial Statistics geoprocessing tool should be used to accomplish this task?

AAverage Nearest Neighbor

BCentral Feature

CMean Center

DStandard Distance

Show Suggested Answer

Suggested Answer: A

by Gail at Dec 21, 2023, 07:14 PM

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Bulah

11 days ago

This question is making my head spin like a top! Maybe I should just use a Ouija board to figure out the answer. Or perhaps a crystal ball would work better for spatial analyses.

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Jacquline

15 days ago

Hold up, is this a trick question? I mean, if we're looking for outliers, wouldn't the Average Nearest Neighbor tool be the way to go? It's like finding the black sheep in the herd, right?

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Dominga

20 days ago

I'm stumped on this one. All the options sound somewhat relevant, but I'm not sure which one is the best fit. Guess I'll have to do some more research on these spatial analysis tools.

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Bonita

2 days ago

I think it might be C) Mean Center.

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An

4 days ago

A) Average Nearest Neighbor

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Tenesha

26 days ago

Interesting problem. I'm not sure Standard Distance is the right tool though. Wouldn't Mean Center be a better choice to first find the mean center, and then we could use that to identify the outliers?

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Phillip

27 days ago

I'm not sure, but I think D) Standard Distance might also be useful in identifying spatial outliers based on the distance from the mean center.

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Carol

29 days ago

I agree with Fausto. Mean Center calculates the center of the features, so it can help identify spatial outliers.

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Sunshine

30 days ago

Hmm, the key here is to identify spatial outliers. I think Standard Distance would be the way to go since it calculates the standard distance around the mean center, which could help identify the outliers.

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