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Databricks Databricks-Certified-Professional-Data-Scientist Exam Dumps - Actual Questions Answers

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Databricks-Certified-Professional-Data-Scientist Questions and Answers

Question # 1

Suppose you have been given two Random Variables X and Y, whose joint distribution is already known, the marginal distribution of X is simply the probability distribution of X averaging over information about Y. It is the probability distribution of X when the value of Y is not known. So how do you calculate the marginal distribution of X

A.

This is typically calculated by summing the joint probability distribution over Y.

B.

This is typically calculated by integrating the joint probability distribution over Y

C.

This is typically calculated by summing (In case of discrete variable) the joint probability distribution over Y

D.

This is typically calculated by integrating(ln case of continuous variable) the joint probability distribution over Y.

Question # 2

Which of the following question statement falls under data science category?

A.

What happened in last six months?

B.

How many products have been sold in a last month?

C.

Where is a problem for sales?

D.

Which is the optimal scenario for selling this product?

E.

What happens, if these scenario continues?

Question # 3

Scenario: Suppose that Bob can decide to go to work by one of three modes of transportation,

car, bus, or commuter train. Because of high traffic, if he decides to go by car. there is a 50% chance he will be late. If he goes by bus, which has special reserved lanes but is sometimes overcrowded, the probability of being late is only 20%. The commuter train is almost never late, with a probability of only 1 %, but is more expensive than the bus.

Suppose that Bob is late one day, and his boss wishes to estimate the probability that he drove to work that day by car. Since he does not know Which mode of transportation Bob usually uses, he gives a prior probability of 1 3 to each of the three possibilities. Which of the following method the boss will use to estimate of the probability that Bob drove to work?

A.

Naive Bayes

B.

Linear regression

C.

Random decision forests

D.

None of the above

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