Dell EMC Data Science and BigData Certification Questions and Answers

Question : Which technique you would be using to solve the below problem statement?
"What is the probability that individual customer will not repay the loan amount?"



1. Classification

2. Clustering

3. Linear Regression

4. Logistic Regression

5. Hypothesis testing


Correct Answer : 4
Explanation:




Question : What type of output generated in case of linear regression?



1. Continuous variable

2. Discrete Variable

3. Any of the Continuous and Discrete variable

4. Values between 0 and 1


Correct Answer : 1
Explanation: Linear regression model generate continuous output variable.




Question : In which of the scenario you can use the linear regression model?
A. Predicting Home Price based on the location and house area
B. Predicting demand of the goods and services based on the weather
C. Predicting tumor size reduction based on input as number of radiation treatment
D. Predicting sales of the text book based on the number of students in state


1. A,B
2. B,C
3. C,D
4. A,B,C
5. A,B,C,D

Correct Answer : 5
Explanation: You can use the linear regression model for predicting the continuous output variable based on the input variables. In all the cases mentioned in the question option, you can see that output
can be predicted based on the input variable.
Option-A : Input : Location, House Area and Output : House Price
Option-B : Input : Weather condition, Output : Demand for the goods and services
Option-C : Input : Number of Radiation Session Output : Tumor Size Reduction
Option-D : Input : Number of students and Output: Sale quantity of text book

Related Questions

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Question : What all are the correct statements with regards to R-squared values in the regression model?
A. R squared values does not indicate whether regression model are adequate.
B. R squared always indicate accuracy of the regression model.
C. Is it possible that R-square can be low for a good regression model.
D. None of above


1. A,B
2. A,C
3. C,D
4. A,D
5. B,D


Question : Which of the following statement is true for the R square value in the regression model?
A. When R square =1 , all the residuals are equal to 0
B. When R square =0, all the residual are equal to 1
C. R square can be increased by adding more variables to the model.
D. R-squared never decreases upon adding more independent variables.


1. A,B
2. B,C
3. C,D
4. A,C,D
5. A,B,C,D


Question : What are the characteristics of the structured data?



1. Data can be co-related with the relationship keys.

2. They can have define data types.

3. These data can be easily queried.

4. It can have well defined schema

5. All of the above



Question : Which of the following are true for semi-structured data?
A. These data can be organized into a specialized repository.
B. These data can be easily stored in RDBMS table
C. These data can have associated metadata and keywords.
D. JSON and XML data are the example of semi-structured data


1. A,B
2. B,C
3. C,D
4. A,D
5. B,D


Question : Which of the following are example of quasi-structured data?
A. XML Data
B. JSON Data
C. Clickstream data
D. Google Search results
E. Any Website web page data for scrapping


1. A,B,C
2. B,C,D
3. C,D,E
4. A,D,E
5. A,C,E


Question : Which of the following are the characteristics of the unstructured data?
A. It can be easily analyzed.
B. It is difficult to query and search these data.
C. It is free-form of data
D. Audio and video files are example of unstructured data
E. These data is scattered and dispersed


1. A,B,C
2. B,C,D
3. C,D,E
4. B,C,D,E
5. A,C,D,E