D-DS-FN-23 Practice Exam and Study Guides – Verified By It-Tests Updated 300 Questions [Q121-Q139] – IT Certification Exam Questions & Answers

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D-DS-FN-23 Practice Exam and Study Guides – Verified By It-Tests Updated 300 Questions

2024 Updated Verified Pass D-DS-FN-23 Study Guides & Best Courses

NO.121 Refer to the exhibit.

You have created a density plot of purchase amounts from a retail website as shown.
What should you do next?

Recreate the plot using the barplot() function

Use the rug() function to add elements to the plot

Recreate the density plot using a log normal distribution of the purchase amount data

Reduce the sample size of the purchase amount data used to create the plot

NO.122 You have been assigned to do a study of the daily revenue effect of a pricing model of online transactions.
You have tested all the theoretical models in the previous model planning stage, and all tests have yielded statistically insignificant results.
What is your next step?

Report that the results are insignificant, and reevaluate the original business question.

Run all the models again against a larger sample, leveraging more historical data.

Move forward on the model with the highest significance scores relative to the others.

Modify samples used by the models and iterate until a significant result occurs.

NO.123 You are attempting to find the Euclidean distance between two centroids:
Centroid A’s coordinates: (X = 2, Y = 4)
Centroid B’s coordinates (X = 8, Y = 10)
Which formula finds the correct Euclidean distance?

SQRT((2-8)2+(4-10)2) or 8.49

SQRT(((2-8) x 2) + ((4-10) x 2)) or 12.17

((2-8)2+(4-10)2) or 72

((2-8) x 2 + (4-10) x 2) or 148

NO.124 In time series analysis, what is an indication of a stationary sequence?

Decreasing trend

Increasing trend

Seasonality

Constant variance

NO.125 What is the output format from the Map function of MapReduce?

Key-value pairs

Binary representation of keys concatenated with structured data

Compressed index

Unique key record and separate records of all possible values

NO.126 What is required in a presentation for business analysts?

Budgetary considerations and requests

Operational process changes

Detailed statistical explanation of the applicable modeling theory

The presentation author’s credentials

NO.127 How does Pig’s use of a schema differ from that of a traditional RDBMS?

Pig’s schema is optional

Pig’s schema requires that the data is physically present when the schema is defined

Pig’s schema is required for ETL

Pig’s schema supports a single data type

NO.128 What describes a true limitation of a Logistic Regression method?

Does not handle missing values well

Does not handle redundant variables well

Does not handle correlated variables well

Does not have explanatory values

NO.129 In which phase of the data analytics lifecycle do Data Scientists spend the most time in a project?

Discovery

Data Preparation

Model Building

Communicate Results

NO.130 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?

empdata[empdata$Age > 40, c(“Salary”,”Occupation”)]

empdata[c(“Salary”,”Occupation”), empdata$Age > 40]

empdata[Age > 40, (“Salary”,”Occupation”)]

empdata[, c(“Salary”,”Occupation”)]$Age > 40

NO.131 An IT department deployed a spam filter to reduce the amount of junk e-mail received by its employees.
After six months, they notice that the spam filter is less effective than when initially deployed.
They examine the system running the spam filter and it appears to be operating normally.
What action would improve the effectiveness of the spam filter?

Add more processing power to the spam filtering system

Add more storage to the spam filtering system

Create a linear regression model to calculate the probability of an email being spam

Retrain the spam filter with newer examples of spam emails

NO.132 A data scientist plans to classify the sentiment polarity of 10, 000 product reviews collected from the Internet.
What is the most appropriate model to use? Suppose labeled training data is available.

Naïve Bayesian classifier

Linear regression

Logistic regression

K-means clustering

NO.133 What are two data categories that represent quantitative data?

Ordinal and interval

Nominal and ratio

Nominal and ordinal

Ratio and interval

NO.134 Which word or phrase completes the statement? A spreadsheet is to a data island as a centralized database for reporting is to a __________?

Data Warehouse

Data Repository

Analytic Sandbox

Data Mart

NO.135 Which key role for a successful analytic project can consult and advise the project team on the value of end results and how these will be used on a day-to-day basis?

Business User

Project Manager

Data Scientist

Business Intelligence Analyst

NO.136 You have created a scatterplot of two continuous variables for 2000 records. You want to add a line to the scatterplot to check linearity of the data.
Which function would best address this need?

abline()

glm()

hist()

lm()

NO.137 You have used k-means clustering to classify behavior of 100, 000 customers for a retail store. You decide to use household income, age, gender and yearly purchase amount as measures.
You have chosen to use 8 clusters and notice that 2 clusters only have 3 customers assigned.
What should you do?

Decrease the number of clusters

Increase the number of clusters

Decrease the number of measures used

Identify additional measures to add to the analysis

NO.138 Which chart type is the most effective way to show trends over time?

Line Chart

Bar Chart

Stacked Bar Chart

Histogram

NO.139 You have been assigned to do a study of the daily revenue effect of a pricing model of online transactions.
All the data currently available to you has been loaded into your analytics database; revenue data, pricing data, and online transaction data.
You find that all the data comes in different levels of granularity. The transaction data has timestamps (day, hour, minutes, seconds), pricing is stored at the daily level, and revenue data is only reported monthly.
What is your next step?

Report back to the business owner that the current data model does not support the business question.

Interpolate a daily model for revenue from the monthly revenue data.

Aggregate all data to the monthly level in order to create a monthly revenue model.

Disregard revenue as a driver in the pricing model, and create a daily model based on pricing and transactions only.

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