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You don't have to install excessive plugins or software to attempt this EMC D-DS-FN-23 practice test. This version of D-DS-FN-23 practice exam is supported by these operating systems: Windows, Mac, iOS, Linux, and Android. It is a customizable EMC D-DS-FN-23 Practice Exam. It means takers can change its duration and D-DS-FN-23 practice test question numbers. The actual EMC D-DS-FN-23 exam environment that the practice exam creates is beneficial to counter Dell Data Science Foundations (D-DS-FN-23) exam anxiety.

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

Topic
Details

Topic 1

Advanced Analytics for Big Data - Technology and Tools: This section of the exam measures the skills of a Data Science Enthusiast and addresses the technological challenges associated with Big Data. It introduces tools and technologies such as MapReduce, Hadoop, the Hadoop ecosystem, in-database analytics, SQL essentials, and advanced SQL techniques like window functions and MADlib.

Topic 2

Big Data, Analytics, and the Data Scientist Role: This section of the exam measures the skills of a Data Science Enthusiast and covers the basic concepts of Big Data, including its defining characteristics and the business drivers behind its rise. It also introduces the role of the Data Scientist, highlighting the critical skills needed in the data science field.

Topic 3

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.

EMC Dell Data Science Foundations Sample Questions (Q225-Q230):

NEW QUESTION # 225
You have scored your Naïve Bayesian Classifier model on "hold out" test data for cross validation. You have determined the way the samples scored and have tabulated them as shown in the exhibit.

What are the Precision and Recall rates of the model?

A. Precision = 288/262 Recall = 277/262
B. Precision =262/288 Recall = 262/277
C. Precision = 262/277 Recall = 262/288
D. Precision = 277/262 Recall = 288/262

Answer: C

NEW QUESTION # 226
What is a distinct property of Logistic Regression compared with Linear Regression?

A. Logistic Regression returns probability estimates of an event
B. Logistic Regression works well with discrete variables that have many distinct values
C. Logistic Regression is robust with redundant or correlated variables
D. Logistic Regression handles missing values well

Answer: A

NEW QUESTION # 227
Which word or phrase completes the statement; "Excessive emphasis color is to Bar chart as
__________________."?

A. Multicollinearity is to OLS
B. Multicollinearity is to serial correlation
C. Confidence is to leverage
D. Confidence interval is to regression

Answer: A

NEW QUESTION # 228
In time series analysis, what function is examined to identify the order of the autoregressive component of an ARIMA model?

A. Logistic function
B. Normal distribution function
C. Partial autocorrelation function
D. Lognormal distribution function

Answer: C

Explanation:
The Partial Autocorrelation Function (PACF) is examined to identify the order of the autoregressive (AR) component in an ARIMA model. It helps determine how much of the autocorrelation is explained by previous lags, assisting in selecting the appropriate AR order.

NEW QUESTION # 229
Your customer provided you with 2, 000 unlabeled records and asked you to separate them into three groups.
What is the correct analytical method to use?

A. Naive Bayesian classification
B. Logistic regression
C. Linear regression
D. K-means clustering

Answer: D

NEW QUESTION # 230
......

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