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EMC Associate - Data Science and Big Data Analytics v2 Exam Sample Questions (Q203-Q208):

NEW QUESTION # 203
Consider the following itemsets:
(hat, scarf, coat)
(hat, scarf, coat, gloves)
(hat, scarf, gloves)
(hat, gloves)
(scarf, coat, gloves)
If the minimum support is 50%, what represents the complete list of frequent 2-itemsets?
Response:

A. (hat, scarf), (hat, gloves), (scarf, gloves), (scarf, coat)
B. (scarf, gloves), (scarf, coat) (hat, gloves)
C. (hat, scarf), (scarf, coat), (coat, gloves)
D. (hat, scarf), (hat, gloves)

Answer: A

NEW QUESTION # 204
A Data Scientist is assigned to build a model from a reporting data warehouse. The warehouse contains data collected from many sources and transformed through a complex, multi-stage ETL process.
What is a concern the data scientist should have about the data?
Response:

A. It is too centralized
B. It is too processed
C. It is not structured
D. It is not normalized

Answer: B

NEW QUESTION # 205
If R factors are categorical variables, which data classification level are they most closely related?
Response:

A. Nominal
B. Interval
C. Ratio
D. Ordinal

Answer: A

NEW QUESTION # 206
You have been assigned to perform a study of the daily revenue effect of a pricing model of online transactions. All the data currently available has been loaded into an analytics database.
This data includes revenue data, pricing data, and online transaction dat a. You have completed a thorough univariate analysis of all data and have decided that there are three different models you want to test. Preliminary results show that all models have equally effective results.
What is the next step?
Response:

A. Select the model that demonstrates the most sophisticated technique and accuracy
B. Develop all three models and perform model selection in the next step of the process
C. Prioritize models by complexity and feasibility, and proceed with the most feasible
D. Identify which model the business owner wants and proceed with that model

Answer: C

NEW QUESTION # 207
When would you prefer a Naive Bayes model to a logistic regression model for classification?
Response:

A. When you need to estimate the probability of an outcome, not just which class it is in.
B. When all the input variables are numerical.
C. When some of the input variables might be correlated.
D. When you are using several categorical input variables with over 1000 possible values each.

Answer: D

NEW QUESTION # 208
......

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