Salesforce ANC-201 Exam - Topic 5 Question 11 Discussion

Actual exam question for Salesforce's ANC-201 exam

Question #: 11
Topic #: 5

[All ANC-201 Questions]

After the initial creation of a model, the first model insight explains

93% of the variation of the outcome variable. This is unusually high.

What is the most likely reason for this?

AThe dataset contains multiple dominant values.

BThe model contains too many outlier values.

CThe outcome variable may be causing data leakage.

Show Suggested Answer

Suggested Answer: A

https://help.salesforce.com/articleView?id=bi_security_datasets_row_level.htm

https://help.salesforce.com/articleView?id=managing_the_sharing_model.htm&type=5

by Mirta at Jan 08, 2023, 11:29 AM

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Freeman

5 months ago

Totally agree, data leakage makes the most sense here.

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Rachael

6 months ago

Could be the dataset has dominant values.

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Kristel

6 months ago

Really? 93% seems too good to be true.

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Hyun

6 months ago

I think it's probably data leakage.

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Dong

6 months ago

That's a crazy high percentage!

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Thurman

6 months ago

I feel like I've seen something similar before, but I'm not confident about which option is the best. Maybe I should lean towards data leakage?

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Ezekiel

6 months ago

This reminds me of a practice question where we talked about dominant values. I wonder if option A could be relevant too.

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Venita

6 months ago

I'm not entirely sure, but I think having too many outliers could skew the results, making option B a possibility.

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Jeannetta

7 months ago

I remember discussing data leakage in class, and it seems like option C could be a strong contender here.

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Kelvin

7 months ago

I'm a bit confused by this question. Is it asking about the primary purpose of encryption in cloud object storage? I'll have to review my notes on cloud security to answer this one.

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Paris

7 months ago

This seems straightforward. The question is clearly asking about the maximum one-way latency, so option D, 150 ms one-way, is the correct answer.

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Mila

11 months ago

Wow, 93%? That's like winning the data modeling lottery! I'm hoping the answer is 'The model is so good, it should be illegal.'

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Cristy

10 months ago

A) The dataset contains multiple dominant values.

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Allene

10 months ago

C) The outcome variable may be causing data leakage.

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Gracia

10 months ago

B) The model contains too many outlier values.

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Hoa

10 months ago

A) The dataset contains multiple dominant values.

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Tien

12 months ago

Hey, if I can get 93% variation explained, I'm taking it and running! Doesn't matter how, I'm acing this exam, baby!

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Vivan

10 months ago

C) The outcome variable may be causing data leakage.

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Barabara

10 months ago

B) The model contains too many outlier values.

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Shaquana

11 months ago

A) The dataset contains multiple dominant values.

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Cristal

12 months ago

Data leakage, for sure. It's the only option that makes sense given how high the variation explained is. Someone's been peeking at the test answers!

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Cristina

11 months ago

C) The outcome variable may be causing data leakage.

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In

11 months ago

B) The model contains too many outlier values.

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Cherelle

11 months ago

A) The dataset contains multiple dominant values.

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Dexter

1 year ago

Multiple dominant values, huh? That could definitely skew the results. Gotta watch out for those sneaky outliers too.

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Fernanda

12 months ago

Outliers can throw off the whole model too.

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Rochell

12 months ago

Yeah, multiple dominant values can really mess things up.

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Kimi

1 year ago

But what if the outcome variable is causing data leakage? That could also be a reason.

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Dyan

1 year ago

Wow, 93% variation explained? That's insanely high! My money's on data leakage, it's the most likely culprit here.

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Lacey

11 months ago

I agree, data leakage seems like the most probable reason.

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Bev

11 months ago

C) The outcome variable may be causing data leakage.

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Edda

12 months ago

B) The model contains too many outlier values.

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Renea

1 year ago

A) The dataset contains multiple dominant values.

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Alaine

1 year ago

I agree with Selma. That could explain the high variation explained by the model.

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Selma

1 year ago

I think the dataset contains multiple dominant values.

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