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EMC D-DS-FN-23 Exam Syllabus Topics:

Topic	Details
Topic 1	Data Analytics Lifecycle: This section of the exam measures the skills of an Entry-Level Data Analyst and explains the purpose and phases of the data analytics lifecycle. It includes understanding key activities and roles involved in the discovery, data preparation, model planning, and model building phases to successfully manage analytics projects.
Topic 2	Operationalizing an Analytics Project and Data Visualization Techniques: This section of the exam measures the skills of an Entry-Level Data Analyst and explains best practices for communicating findings and operationalizing analytics projects. It covers effective methods for presenting projects to various audiences and emphasizes the importance of planning and creating impactful data visualizations.
Topic 3	Advanced Analytics - Theory, Application, and Interpretation of Results for Eight Methods: This section of the exam measures the skills of an Entry-Level Data Analyst and covers foundational knowledge in various advanced analytics methods. Topics include the theory, application, and interpretation of K-means clustering, association rules, linear and logistic regression, naïve Bayesian classifiers, decision trees, time series analysis, and text analytics.

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EMC Dell Data Science Foundations Sample Questions (Q350-Q355):

NEW QUESTION # 350
A data scientist wants to add a new categorical variable, X2, into a Linear Regression model Y=b0+b1*X1.
How many terms should be added to the right-hand side of the equation if X2 has four possible values?

A. 0
B. 1
C. 2
D. 3

Answer: B

NEW QUESTION # 351
Refer to the exhibit.

In the exhibit, the x-axis represents the derived probability of a borrower defaulting on a loan. Also in the exhibit, the pink represents borrowers that are known to have not defaulted on their loan, and the blue represents borrowers that are known to have defaulted on their loan.
Which analytical method could produce the probabilities needed to build this exhibit?

A. Logistic Regression
B. Association Rules
C. Linear Regression
D. Discriminant Analysis

Answer: A

NEW QUESTION # 352
During the data preparation phase, you notice a high correlation between average spend on video games, age of players, and number of science fiction shows watched.
Which technique could you use to address the three correlated variables?

A. Drop the three variables to improve the model
B. Use scaling to make the three variables equivalent in size
C. Combine the three variables into one new variable
D. Square the three variables to remove the correlation

Answer: C

NEW QUESTION # 353
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?

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

Answer: C

NEW QUESTION # 354
Which statement about linear regression is correct?

A. Outcome variable is discrete
B. All input variables must be discrete
C. Outcome variable is continuous
D. All input variables must be continuous

Answer: C

NEW QUESTION # 355
......

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Valid D-DS-FN-23 Exam Format, D-DS-FN-23 Exam Simulator Online

EMC D-DS-FN-23 Exam Syllabus Topics:

Pass the EMC D-DS-FN-23 certification exam with flying colors

EMC Dell Data Science Foundations Sample Questions (Q350-Q355):

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