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Databricks Certified Professional Data Scientist Exam - Topic 2 Question 57 Discussion

Actual exam question for Databricks's Databricks Certified Professional Data Scientist exam
Question #: 57
Topic #: 2
[All Databricks Certified Professional Data Scientist Questions]

You have modeled the datasets with 5 independent variables called A,B,C,D and E having relationships which is not dependent each other, and also the variable A,B and C are continuous and variable D and E are discrete (mixed mode).

Now you have to compute the expected value of the variable let say A, then which of the following computation you will prefer

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Suggested Answer: B

by Nobuko at Apr 24, 2024, 03:24 PM

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Tomoko
3 months ago
Transformation seems a bit off for this context.
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Jani
3 months ago
Surprised that Generalization isn’t the answer here!
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Cherry
3 months ago
Wait, isn’t Differentiation also a valid option?
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Sheron
4 months ago
Totally agree, that’s the standard approach!
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Zack
4 months ago
I’d go with Integration for expected value.
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Johnetta
4 months ago
Generalization seems off for this question; I believe integration is the right choice for calculating expected values, especially with continuous data.
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Emile
4 months ago
I’m a bit confused about whether differentiation could apply here. I thought it was more about rates of change, not expected values.
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Maile
4 months ago
I remember practicing a similar question where we had to find expected values, and integration was definitely the method used for continuous variables like A.
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Paola
5 months ago
I think we might need to use integration to compute the expected value of A since it's a continuous variable, but I'm not entirely sure.
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Herman
5 months ago
I'm leaning towards generalization here. The question doesn't provide much detail on the specific relationships between the variables, so a more general approach like generalization might be better suited to handle the complexity of the data structure. That way, we can make fewer assumptions and still compute the expected value of A.
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Sheldon
5 months ago
Based on the information provided, I would go with transformation. Since the variables A, B, and C are continuous, we can likely transform them to a standard normal distribution and then compute the expected value of A using that. The discrete variables D and E might require a different approach, but transformation seems like the most appropriate option for the continuous part.
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Lina
5 months ago
Hmm, I'm a bit confused on this one. The question mentions mixed mode data with both continuous and discrete variables. I'm not sure if integration is the right approach for that case. Maybe we need to consider a different computation method that can handle the mixed data structure.
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Adelina
5 months ago
I think integration would be the best approach here since we need to compute the expected value of the continuous variable A. The question mentions the variables have relationships, so we'll need to integrate over the joint distribution to find the expected value.
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Charlie
5 months ago
This is a tricky one. I'll need to think through the characteristics of relational databases to determine which of these options doesn't fit.
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Rebbecca
5 months ago
Okay, I've got this. A System DSN is a data source that's not tied to a specific user account. It's a shared resource that anyone with the right access can use. I'm pretty confident that option A is the correct answer here.
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Talia
5 months ago
The instructions give a few different ways to unhide the worksheet, so I'll try to remember the key steps like using Ctrl+Shift to select all the tabs.
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Theodora
5 months ago
I'm confused about customer sites. Can they really be linked to multiple VRFs, or am I mixing that up with something else?
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Chau
10 months ago
I'm not sure what's more surprising - the fact that differentiation is an option, or the fact that someone might actually choose it. Integration all the way!
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Graciela
8 months ago
Transformation could also be a good option for computing the expected value of variable A.
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Yen
8 months ago
Differentiation seems like an odd choice in this scenario.
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William
9 months ago
I agree, integration is the way to go for computing expected values.
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Bev
10 months ago
I'm with Eliz on this one. Differentiation? What were they thinking? Integration is the way to solve this problem.
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Olga
9 months ago
Integration allows for a more accurate calculation in this case.
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Dierdre
9 months ago
Differentiation might not be the right approach in this scenario.
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Justine
10 months ago
I agree, Integration is the most suitable method for this type of computation.
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Fernanda
10 months ago
I think Integration is the best way to compute the expected value of variable A.
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Eladia
10 months ago
Transformation and generalization are just not relevant in this context. I'll stick with the good old integration method.
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Martina
10 months ago
Integration is definitely the most suitable method for this calculation.
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James
10 months ago
I agree, integration is the way to go for computing the expected value of variable A.
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Louis
10 months ago
I would go with Transformation, as it can help in handling both continuous and discrete variables effectively.
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Lisbeth
10 months ago
I agree with Dahlia, Integration seems like the most appropriate computation method in this scenario.
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Eliz
11 months ago
Differentiation? Really? That's for finding the rate of change, not the expected value. This is a clear integration problem.
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Glory
9 months ago
Integration is used to find the expected value, not Differentiation.
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Micah
9 months ago
Differentiation is not the right choice here, it's definitely Integration.
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Jani
9 months ago
I agree, Integration is the correct method for this computation.
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Xuan
10 months ago
I think Integration is the way to go for computing the expected value.
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Catarina
11 months ago
Integration is the way to go here. Since the variable A is continuous, we need to compute the expected value by integrating the probability density function.
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Dahlia
11 months ago
I think I would prefer Integration to compute the expected value of variable A.
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