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Exam Code: E20-007Exam Name: Data Science and Big Data Analytics
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E20-007 Exam Cost Total Q&A: 165 Questions and Answers
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Exam Code: E20-018Exam Name: Virtualized Data Center and Cloud Infrastructure Design Specialist
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Exam Code: E22-290Exam Name: EMC Data Domain Deduplication, Backup and Recovery Exam
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NO.1 What is an appropriate data visualization to use in a presentation for an analyst audience?
A. Pie chart
B. Area chart
C. Stacked bar chart
D. ROC curve
Answer: D
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NO.2 In R, functions like plot() and hist() are known as what?
A. generic functions
B. virtual methods
C. virtual functions
D. generic methods
Answer: B
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NO.3 Which word or phrase completes the statement? Data-ink ratio is to data visualization as __________ .
A. Confusion matrix is to classifier
B. Data scientist is to big data
C. Seasonality is to ARIMA
D. K-means is to Naive Bayes
Answer: A
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NO.4 When creating a presentation for a technical audience, what is the main objective?
A. Show that you met the project goals
B. Show how you met the project goals
C. Show if the model will meet the SLA
D. Show the technique to be used in the production environment
Answer: B
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NO.5 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}
Answer: A
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NO.6 Which type of numeric value does a logistic regression model estimate?
A. Probability
B. A p-value
C. Any integer
D. Any real number
Answer: A
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NO.7 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
Answer: C
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NO.8 You are using MADlib for Linear Regression analysis. Which value does the statement return?
SELECT (linregr(depvar, indepvar)).r2 FROM zeta1;
A. Goodness of fit
B. Coefficients
C. Standard error
D. P-value
Answer: A
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