Databricks Certified Professional Data Scientist Exam - Topic 3 Question 93 Discussion

Actual exam question for Databricks's Databricks Certified Professional Data Scientist exam

Question #: 93
Topic #: 3

[All Databricks Certified Professional Data Scientist Questions]

Marie is getting married tomorrow, at an outdoor ceremony in the desert. In recent years, it has

rained only 5 days each year. Unfortunately, the weatherman has predicted rain for tomorrow. When it actually rains, the weatherman correctly forecasts rain 90% of the time. When it doesn't rain, he incorrectly forecasts rain 10% of the time. Which of the following will you use to calculate the probability whether it will rain on the

day of Marie's wedding?

ANaive Bayes

CRandom Decision Forests

BLogistic Regression

DAll of the above
The sample space is defined by two mutually-exclusive events - it rains or it does not rain. Additionally, a third event occurs when the weatherman predicts rain. You should consider Bayes' theorem when the following conditions exist.
* The sample space is partitioned into a set of mutually exclusive events {A1, A2,... :An}.
* Within the sample space, there exists an event B: for which P(B) > 0.
* The analytical goal is to compute a conditional probability of the form: P( Ak B).

Show Suggested Answer

Suggested Answer: A

by Delmy at Jan 23, 2026, 03:13 PM

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Sherell

1 day ago

Haha, 90% accuracy? That weatherman must be the best in the business. Bayes' Theorem is the way to solve this for sure.

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Miesha

6 days ago

Bayes' Theorem is the answer, no doubt. I bet the weatherman wishes he had a better track record though!

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Adell

11 days ago

Hmm, I'm thinking Bayes' Theorem too. The weather forecast data seems like the key to cracking this one.

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Dorthy

17 days ago

Bayes' Theorem is the way to go here. Gotta love that conditional probability!

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Deja

22 days ago

I’m a bit lost on how to set up the calculations. Do we need to consider both the probability of rain and the accuracy of the forecast?

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Domitila

27 days ago

This question reminds me of a similar practice problem we did about weather predictions. I think we might need to calculate the overall probability of rain first.

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Micaela

2 months ago

I'm not entirely sure, but I remember something about using prior probabilities and updating them based on new evidence.

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Alaine

2 months ago

I think we need to use Bayes' theorem here since we have conditional probabilities involved.

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Oliva

2 months ago

Ugh, probability questions are the worst. There are so many different formulas to remember. I'll just have to take it slow, read through the details carefully, and try my best to figure out the right approach.

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Shawna

2 months ago

This seems tricky, but I remember learning about these types of probability problems in class. I'll need to be really careful to identify all the given information and use it properly.

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Val

2 months ago

Okay, I think I've got this. The key is identifying the relevant probabilities and plugging them into the Bayes' Theorem equation. I'm feeling pretty confident I can solve this one.

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Gregg

3 months ago

Hmm, I'm a bit confused. There's a lot of information here about the weather forecasts. I'll need to really break this down step-by-step to make sure I understand it correctly.

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Derrick

3 months ago

This looks like a Bayes' Theorem problem. I'll need to find the prior probability, the likelihood, and then use the formula to calculate the posterior probability.

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