Cloudera Databricks Data Science Certification Questions and Answers (Dumps and Practice Questions)

Question : You are working on a problem where you have to predict whether the claim is done valid or not.
And you find that most of the claims which are having spelling errors as well as corrections in the manually
filled claim forms compare to the honest claims. Which of the following technique is suitable to find
out whether the claim is valid or not?

1. Naive Bayes
2. Logistic Regression
3. Random Decision Forests
4. Any one of the above



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In this problem you have been given high-dimensional independent variables like texts, corrections, test results etc. and you have to predict either valid or not valid (One of two). So all of the below technique can be applied to this problem.

Support vector machines
Naive Bayes
Logistic regression
Random decision forests






Question : . Bayes' Theorem allows you to look at an event that has already happened and make an
educated guess about the chain of events that may have led up to that event

1. True
2. False


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Question :

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.

Question : 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?


1. Naive Bayes
2. Linear regression
3. Random decision forests
4. None of the above



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Bayes' theorem (also known as Bayes' rule) is a useful tool for calculating conditional probabilities.

Related Questions

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Question :Suppose there are three events then which formula must always be equal to P(E|E,E)?


1. P(E1,E2,E3)P(E1) / P(E2,E3)
2. P(E1,E2,E3) / P(E2,E3)
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4. P(E1,E2|E3)P(E3)
5. P(E1,E2,E3)P(E2)P(E3)



Question : Which of the following is an example of Gaussian distribution application?

1. If the average man is 175 cm tall with a variance of 6 cm, what is the probability that a man found at random will be 183 cm tall?
2. If the average man is 175 cm tall with a variance of 6 cm and the average woman is 168 cm
tall with a variance of 3cm, what is the probability that the average man will be shorter than the average woman?
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order to ensure that the 99% of all cans have a weight of at least 250 grams?
4. 1 and 2 only
5. Both 1 and 2





Question : It was found that the mean length of parts produced by a lathe was . mm with a standard deviation of . mm.
Find the probability that a part selected at random would have a length
between 20.03 mm and 20.08 mm



1. .11
2. 0.33
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4. 0.77



Question : . It was found that the mean length of parts produced by a lathe was . mm
with a standard deviation of 0.02 mm. Find the probability that a part selected at random would have a length less than 20.01 mm



1. 0.0228
2. 0.0338.
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4. 0.0558.


Question : It was found that the mean length of parts produced by a lathe was . mm with a
standard deviation of 0.02 mm. Find the probability that a part selected at random would have a length
between 20.06 mm and 20.07 mm

1. 0.1298
2. 0.1398
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4. 0.1598





Question : It was found that the mean length of parts produced by a lathe was . mm with a standard deviation of . mm.
Find the probability that a part selected at random would have a length greater than 20.09 mm.


1. 0.0228
2. 0.0338
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4. 0.0558