Verified D-DS-FN-23 exam dumps Q&As with Correct 358 Questions and Answers [Q37-Q59]

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Verified D-DS-FN-23 exam dumps Q&As with Correct 358 Questions and Answers

EMC D-DS-FN-23 Test Engine PDF - All Free Dumps from TestPassKing


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

TopicDetails
Topic 1
  • 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 2
  • 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 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.
Topic 4
  • Initial Analysis of the Data: This section of the exam measures the skills of a Data Science Enthusiast and focuses on the first steps in analyzing data. It explains how basic R commands are used for exploration, discusses important statistical measures and visualizations, and describes hypothesis testing techniques for evaluating models.

 

NEW QUESTION # 37
In a user-defined aggregate function, what is FFUNC?

  • A. State transition function
  • B. Window function
  • C. Segment-level calculation function
  • D. Optional final calculation function

Answer: D

Explanation:
In a user-defined aggregate function (UDAF), FFUNC refers to the optional final calculation function. It is used to perform any final calculation or transformation on the aggregated result before it is returned to the user.


NEW QUESTION # 38
Which statement about linear regression is correct?

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

Answer: B


NEW QUESTION # 39
In time series analysis, what function is examined to identify the order of the moving average component of an ARIMA model?

  • A. Geometric mean function
  • B. Autocorrelation function
  • C. Exponential function
  • D. Arithmetic mean function

Answer: B


NEW QUESTION # 40
Refer to the exhibit.

The exhibit shows four graphs labeled as Fig A thorough Fig D.
Which figure represents the entropy function relative to a Boolean classification and is represented by the formula shown in Exhibit?

  • A. Fig-C
  • B. Fig-D
  • C. Fig-A
  • D. Fig-B

Answer: C


NEW QUESTION # 41
What is the difference between the array and list data structures in R?

  • A. Arrays can contain different data types;
    Lists can contain only the same data type
  • B. Arrays contain only the same data type;
    Lists can contain different data types
  • C. Arrays are N-dimensional;
    Lists are only 2-dimensional
  • D. Arrays are only 2-dimensional;
    Lists are N-dimensional

Answer: B


NEW QUESTION # 42
What converts SQL-like commands into either Tez, Spark, or MapReduce jobs that are submitted to the Hadoop cluster?

  • A. Mahout
  • B. Hive
  • C. Pig
  • D. HBase

Answer: B

Explanation:
Hive converts SQL-like commands into execution plans that run as Tez, Spark, or MapReduce jobs on a Hadoop cluster, enabling users to query large datasets using a familiar query language.


NEW QUESTION # 43
What should be subtracted to remove a simple linear trend from a time series?

  • A. Expected squared deviation
  • B. Expected absolute deviation
  • C. Cubic-spline
  • D. Least-squares-fit line

Answer: D


NEW QUESTION # 44
The graph represents the plot of WSS as a function of K for a K-means clustering analysis you performed.

Which point in the graph represents the most optimal value of K?

  • A. C
  • B. B
  • C. D
  • D. A

Answer: A


NEW QUESTION # 45
Which process in text analysis can be used to reduce dimensionality?

  • A. Sorting
  • B. Digitizing
  • C. Stemming
  • D. Parsing

Answer: C


NEW QUESTION # 46
Refer to the Exhibit.

You are going into a meeting where you anticipate your manager will have a question on your dataset.
Specifically, your manager will want to know about customers that are classified as renters with a good credit status.
In order to prepare for the meeting, you create a rule: RENTER => GOOD CREDIT.
What is the confidence of this rule?

  • A. 63%
  • B. 41%
  • C. 73%
  • D. 18%

Answer: A


NEW QUESTION # 47
In a user-defined aggregate function, what is SFUNC?

  • A. Final calculation function
  • B. Window function
  • C. Segment-level calculation function
  • D. State transition function

Answer: D


NEW QUESTION # 48

Refer to the exhibit, which shows pairwise counts for items purchased together.
Consider the following association rule: Milk -> Eggs
What is value of the lift?

  • A. 0
  • B. 1.18
  • C. 70.81
  • D. 0.264

Answer: B

Explanation:

P(Milk#Eggs) is the probability of both Milk and Eggs being bought together, which is the count for Milk and Eggs (110).
P(Milk)) is the probability of Milk being bought, which is the total for Milk (233) divided by the grand total (374).
P(Eggs) is the probability of Eggs being bought, which is the total for Eggs (150) divided by the grand total (374).

The value of the lift for the association rule Milk -> Eggs is approximately 1.18.


NEW QUESTION # 49
Which ROC curve represents a perfect model fit?
A)

B)

C)

D)

  • A. Exhibit B
  • B. Exhibit A
  • C. Exhibit C
  • D. Exhibit D

Answer: B


NEW QUESTION # 50
Which word or phrase completes the statement? Mahout is to Hadoop as MADlib is to _______.

  • A. Excel
  • B. PostgreSQL
  • C. SAS
  • D. R

Answer: B


NEW QUESTION # 51
In linear regression modeling, which action can be taken to improve the linearity of the relationship between the dependent and independent variables?

  • A. Apply a transformation to a variable
  • B. Use a different statistical package
  • C. Change the units of measurement on the independent variable
  • D. Calculate the R-Squared value

Answer: A


NEW QUESTION # 52
You have an automotive database containing numeric characteristics such as engine size, horsepower, and top speed.
Which technique could you use to group similar cars together?

  • A. Naïve Bayes classifier
  • B. Logistic regression
  • C. Association rules
  • D. K-means clustering

Answer: D


NEW QUESTION # 53
Which relationship holds for a confusion matrix?

  • A. Precision = 1 - False Positive Ratio
  • B. Recall = 1 - False Negative Ratio
  • C. Recall = 1 - False Positive Ratio
  • D. Precision = 1 - False Negative Ratio

Answer: B


NEW QUESTION # 54
In R, functions like plot() and hist() are known as what?

  • A. generic methods
  • B. virtual functions
  • C. generic functions
  • D. virtual methods

Answer: D


NEW QUESTION # 55
After which phase of the data analytics lifecycle should you determine if the model needs any recalibration?

  • A. Data preparation
  • B. Model planning
  • C. Discovery
  • D. Operationalize

Answer: D

Explanation:
Recalibration of the model should be assessed during the Operationalize phase, as this is when the model is deployed and monitored in real-world conditions, making it easier to identify if it requires adjustments based on its performance.


NEW QUESTION # 56
A data scientist is given an R data frame (i.e., empdata) with the following columns: Age Salary Occupation Education Gender The scientist wants to examine only the Salary and Occupation columns for ages greater than '40'.
Which command extracts the appropriate rows and columns from the data frame?

  • A. empdata[, c("Salary","Occupation")]$Age > 40
  • B. empdata[c("Salary","Occupation"), empdata$Age > 40]
  • C. empdata[empdata$Age > 40, c("Salary","Occupation")]
  • D. empdata[Age > 40, ("Salary","Occupation")]

Answer: C


NEW QUESTION # 57
What describes a true property of Logistic Regression method?

  • A. It works well with discrete variables that have many distinct values.
  • B. It is robust with redundant variables and correlated variables.
  • C. It works well with variables that affect the outcome in a discontinuous way.
  • D. It handles missing values well.

Answer: B


NEW QUESTION # 58
Assume that you have a data frame in R.
Which function would you use to display descriptive statistics about this variable?

  • A. levels
  • B. summary
  • C. attributes
  • D. str

Answer: B


NEW QUESTION # 59
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