E20-007 Questions And Answers
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Exam Name: Data Science and Big Data Analytics
Updated: 2020-09-20
Q & A: 198
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Question No : 1
What describes a true limitation of Logistic Regression method?
A. It does not handle missing values well.
B. It does not handle redundant variables well.
C. It does not handle correlated variables well.
D. It does not have explanatory values.
A. It does not handle missing values well.
B. It does not handle redundant variables well.
C. It does not handle correlated variables well.
D. It does not have explanatory values.
Answer: A
Question No : 2
Refer to the exhibit.
Click on the calculator icon in the upper left corner. An analyst is searching a corpus of documents for the topic "solid state disk". In the Exhibit, Table A provides the inverse document frequency for each term across the corpus. Table B provides each term's frequency in four documents selected from corpus. Which of the four documents is most relevant to the analyst's search?
A. Document B
B. Document A
C. Document C
D. Document D
Click on the calculator icon in the upper left corner. An analyst is searching a corpus of documents for the topic "solid state disk". In the Exhibit, Table A provides the inverse document frequency for each term across the corpus. Table B provides each term's frequency in four documents selected from corpus. Which of the four documents is most relevant to the analyst's search?
A. Document B
B. Document A
C. Document C
D. Document D
Answer: A
Question No : 3
Refer to the Exhibit.
In the Exhibit, the table shows the values for the input Boolean attributes "A", "B", and "C". It also shows the values for the output attribute "class". Which decision tree is valid for the data?
A. Tree B
B. Tree A
C. Tree C
D. Tree D
In the Exhibit, the table shows the values for the input Boolean attributes "A", "B", and "C". It also shows the values for the output attribute "class". Which decision tree is valid for the data?
A. Tree B
B. Tree A
C. Tree C
D. Tree D
Answer: A
Question No : 4
Consider a scale that has five (5) values that range from ¡°not important¡± to ¡°very important¡±. Which data classification best describes this data?
A. Ordinal
B. Nominal
C. Real
D. Ratio
A. Ordinal
B. Nominal
C. Real
D. Ratio
Answer: A
Question No : 5
What is a property of window functions in SQL commands?
A. They can be used to calculate moving averages over various intervals.
B. They group rows into a single output row.
C. They can be used between the keywords FROM and WHERE in a SELECT command.
D. They don't require ordering of data within a window.
A. They can be used to calculate moving averages over various intervals.
B. They group rows into a single output row.
C. They can be used between the keywords FROM and WHERE in a SELECT command.
D. They don't require ordering of data within a window.
Answer: A
Question No : 6
What is required in a presentation for business analysts?
A. Budgetary considerations and requests
B. Operational process changes
C. Detailed statistical explanation of the applicable modeling theory
D. The presentation author's credentials
A. Budgetary considerations and requests
B. Operational process changes
C. Detailed statistical explanation of the applicable modeling theory
D. The presentation author's credentials
Answer: B
Question No : 7
Consider a database with 4 transactions:
Transaction 1: {cheese, bread, milk}
Transaction 2: {soda, bread, milk}
Transaction 3: {cheese, bread}
Transaction 4: {cheese, soda, juice}
You decide to run the association rules algorithm where minimum support is 50%. Which rule has a confidence at least 50%?
A. {cheese} => {bread}
B. {juice} => {cheese}
C. {milk} => {soda}
D. {soda} => {milk}
Transaction 1: {cheese, bread, milk}
Transaction 2: {soda, bread, milk}
Transaction 3: {cheese, bread}
Transaction 4: {cheese, soda, juice}
You decide to run the association rules algorithm where minimum support is 50%. Which rule has a confidence at least 50%?
A. {cheese} => {bread}
B. {juice} => {cheese}
C. {milk} => {soda}
D. {soda} => {milk}
Answer: A
Question No : 8
Refer to the exhibit.
Which type of data issue would you suspect based on the exhibit?
A. "Saturated" data, indicating potential issues with data definitions
B. Incomplete data, indicating potential issues with data transmission
C. Mis-scaled data, indicating potential issues with data entry
D. The exhibit does not raise any obvious concerns with the data.
Which type of data issue would you suspect based on the exhibit?
A. "Saturated" data, indicating potential issues with data definitions
B. Incomplete data, indicating potential issues with data transmission
C. Mis-scaled data, indicating potential issues with data entry
D. The exhibit does not raise any obvious concerns with the data.
Answer: A
Question No : 9
You are using the Apriori algorithm to determine the likelihood that a person who owns a home has a good credit score. You have determined that the confidence for the rules used in the algorithm is > 75%. You calculate lift = 1.011 for the rule, "People with good credit are homeowners". What can you determine from the lift calculation?
A. Support for the association is low
B. Leverage of the rules is low
C. The rule is coincidental
D. The rule is true
A. Support for the association is low
B. Leverage of the rules is low
C. The rule is coincidental
D. The rule is true
Answer: C
Question No : 10
What is a property of windows functions in SQL commands?
A.Used to calculate moving averages over various intervals
B.Group rows into a single output row
C.Used between the keywords FROM and WHERE in a SELECT command
D.Ordering data within a window is not required
A.Used to calculate moving averages over various intervals
B.Group rows into a single output row
C.Used between the keywords FROM and WHERE in a SELECT command
D.Ordering data within a window is not required
Answer: A
Question No : 11
Which type of numeric value does a logistic regression model estimate?
A. Probability
B. A p-value
C. Any integer
D. Any real number
A. Probability
B. A p-value
C. Any integer
D. Any real number
Answer: A
Question No : 12
You have used k-means clustering to classify behavior of 100, 000 customers for a retail store. You decide to use household income, age, gender and yearly purchase amount as measures. You have chosen to use 8 clusters and notice that 2 clusters only have 3 customers assigned. What should you do?
A. Decrease the number of clusters
B. Increase the number of clusters
C. Decrease the number of measures used
D. Identify additional measures to add to the analysis
A. Decrease the number of clusters
B. Increase the number of clusters
C. Decrease the number of measures used
D. Identify additional measures to add to the analysis
Answer: A
Question No : 13
You are attempting to find the Euclidean distance between two centroids:
Centroid A's coordinates: (X = 2, Y = 4)
Centroid B's coordinates (X = 8, Y = 10)
Which formula finds the correct Euclidean distance?
A. SQRT((2-8)2+(4-10)2) or 8.49
B. SQRT(((2-8) x 2) + ((4-10) x 2)) or 12.17
C. ((2-8)2+(4-10)2) or 72
D. ((2-8) x 2 + (4-10) x 2) or 148
Centroid A's coordinates: (X = 2, Y = 4)
Centroid B's coordinates (X = 8, Y = 10)
Which formula finds the correct Euclidean distance?
A. SQRT((2-8)2+(4-10)2) or 8.49
B. SQRT(((2-8) x 2) + ((4-10) x 2)) or 12.17
C. ((2-8)2+(4-10)2) or 72
D. ((2-8) x 2 + (4-10) x 2) or 148
Answer: A
Question No : 14
To ensure a successful analytic project, which key role can provide business domain expertise with a deep understanding of the data and key performance indicators?
A.Business Intelligence Analyst
B.Project Manager
C.Project Sponsor
D.Business User
A.Business Intelligence Analyst
B.Project Manager
C.Project Sponsor
D.Business User
Answer: A
Question No : 15
What describes a true property of Logistic Regression method?
A. It is robust with redundant variables and correlated variables.
B. It handles missing values well.
C. It works well with discrete variables that have many distinct values.
D. It works well with variables that affect the outcome in a discontinuous way.
A. It is robust with redundant variables and correlated variables.
B. It handles missing values well.
C. It works well with discrete variables that have many distinct values.
D. It works well with variables that affect the outcome in a discontinuous way.
Answer: A