Esri EADP19-001 Exam - 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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Vonda

6 months ago

I’m surprised there’s no tool specifically for outliers!

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Marjory

7 months ago

Agreed, Mean Center is the way to go!

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Jean

7 months ago

Wait, isn't that just for calculating averages?

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Abel

7 months ago

I think Standard Distance is more relevant here.

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Carol

7 months ago

Definitely the Mean Center tool!

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Shaniqua

7 months ago

I feel like the Average Nearest Neighbor might not apply here since we're looking for outliers based on distance from the mean, not proximity to other points.

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Giovanna

8 months ago

I practiced a similar question, and I think the Central Feature tool is more about finding the central point rather than identifying outliers.

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Sena

8 months ago

I'm not entirely sure, but I remember something about standard deviations being involved. Could it be the Standard Distance tool?

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Malcolm

8 months ago

I think we need to find the mean center first, so maybe the Mean Center tool is the right choice?

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Ammie

8 months ago

Hmm, I'm not sure if Average Nearest Neighbor is the right approach here. That's more about clustering, right? I think I need to review the spatial stats tools again.

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Amie

8 months ago

I'm pretty confident the answer is D. Standard Distance seems like the best tool to calculate the distance from the mean center and flag any features beyond one standard deviation.

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Nathalie

8 months ago

I'm a bit confused on this one. Is the Mean Center tool the right choice, since it finds the central feature? Or is that not specific enough for identifying outliers?

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Luis

8 months ago

Okay, I think the Standard Distance tool might be the way to go here. It calculates the standard distance around the mean center, which could help identify features outside that threshold.

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Marleen

8 months ago

Hmm, this seems like a tricky one. I'll need to think through the spatial statistics tools and how they relate to identifying outliers.

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Ty

8 months ago

Hmm, I'm a bit confused. Should we be looking at the Import definition instead? Maybe updating that to include a notification email address could help us identify the bad data rows.

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Albert

8 months ago

Hmm, I'm not entirely sure about the different types of strategies involved in the Process-Centric approach. I'll need to review my notes carefully to make sure I understand the key concepts.

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Ashley

8 months ago

I'm a bit confused by this question. There are a few options that seem relevant, like the Delphi technique or qualitative forecasting. I'll have to carefully read through the details to figure out which one best matches the description.

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Rhea

8 months ago

Okay, this looks like a pretty straightforward capital budgeting problem. I'll need to calculate the net cash flow for the 10th year, which will involve projecting the revenues, costs, and depreciation.

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Bulah

1 year 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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Omega

12 months ago

B) Central Feature

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Vi

12 months ago

I think the correct tool is C) Mean Center.

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Izetta

12 months ago

A) Average Nearest Neighbor

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Jacquline

1 year 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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Stacey

12 months ago

User 3: Yeah, that tool should help identify any spatial outliers.

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Venita

12 months ago

User 2: I agree, it's like finding the black sheep in the herd.

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Cecilia

12 months ago

User 1: I think the Average Nearest Neighbor tool would be the best choice.

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Dominga

1 year 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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Maryrose

1 year ago

I'm leaning towards A) Average Nearest Neighbor.

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Reyes

1 year ago

D) Standard Distance

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Ryann

1 year ago

I agree, C) Mean Center seems like the right choice.

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Lindsey

1 year ago

C) Mean Center

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Blythe

1 year ago

I believe D) Standard Distance could be the one.

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Marshall

1 year ago

B) Central Feature

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Bonita

1 year ago

I think it might be C) Mean Center.

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An

1 year ago

A) Average Nearest Neighbor

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Tenesha

1 year 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

1 year 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

1 year 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

1 year 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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