Salesforce Exam ANC-201 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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Mila

28 days 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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Gracia

2 days ago

B) The model contains too many outlier values.

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Hoa

6 days ago

A) The dataset contains multiple dominant values.

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Tien

1 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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Barabara

2 days ago

B) The model contains too many outlier values.

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Shaquana

8 days ago

A) The dataset contains multiple dominant values.

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Cristal

2 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

13 days ago

C) The outcome variable may be causing data leakage.

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In

21 days ago

B) The model contains too many outlier values.

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Cherelle

30 days ago

A) The dataset contains multiple dominant values.

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Dexter

2 months ago

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

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Fernanda

1 months ago

Outliers can throw off the whole model too.

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Rochell

1 months ago

Yeah, multiple dominant values can really mess things up.

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Kimi

2 months ago

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

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Dyan

2 months 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

30 days ago

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

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Bev

1 months ago

C) The outcome variable may be causing data leakage.

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Edda

1 months ago

B) The model contains too many outlier values.

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Renea

2 months ago

A) The dataset contains multiple dominant values.

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Alaine

2 months ago

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

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Selma

2 months ago

I think the dataset contains multiple dominant values.

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