Data Analytics Skill Assessment

Quizack provides Data Analytics MCQ practice question answers in an interactive format.

Data Analytics MCQ

Learn and practice your skills with our MCQ question answers to improve your knowledge. MCQs list

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Data Analytics Online Quiz

Quizack 10 minutes test will assess your knowledge and give you comprehensive results along feedback.

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Data Analytics PDF Download

Download Free Data Analytics MCQ questions answers PDF to practice and learn while are offline.

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Used by 100s of Jobseekers and students

Used by 100s of Jobseekers and students

Focused questions for skill assessment

Focused questions for skill assessment

Premium questions with correct answers

Premium questions with correct answers

Related Skill Assessment

Data Analytics Skill Assessment:

Data Analytics

Data Analytics is the procedure of analyzing raw data and deciding about how to convert raw data into useful information. So basically, this theory helps organizations or individuals to make sense of data. You can use different techniques and tools to help organizations make decisions and succeed. 

It is always useful to consult the Quizack’s Data Analytics assessment test

We don’t do experiments when it comes to the evaluation or assessment of skills. We entertain our users with absolute knowledge so that they can update their knowledge as per the ongoing standards. We can arrange authentic information because of our industry experts. 

Data Analytics Quiz questions and answers are latest and validated

This particular pool of questions has been produced by subject matter experts after analyzing real exam patterns and ongoing techniques. Now you can prepare yourself in minutes after consulting our Data Analyst Aptitude test questions and answers. Ultimately you will be able to face a relevant IT test, Freelance exam, Job interview, or Pre-Employment assessment.

Quizack’s Data Analytics test questions will cover below topics

  • Data visualization
  • Regression Analysis 
  • Machine learning Techniques
  • Data Manipulation using R
  • Modern data science with R
  • Exploratory Data Analysis
  • MCQ on Data Analytics life cycle

Quizack offers Data Analytics MCQ questions and answers online

You will love to practice questions online through our targeted and integrated testing tools. We have made these tools user-friendly and interactive to provide you real exam testing experience. Amazingly, we have presented questions in the same format as in the real exams. 

“Data Analytics MCQ" is a practice session designed to give you a comprehensive online practice tool. This carries 0 limitations. You will be free to browse questions, skip questions, view the answers, or exit the session at any time. There is no restriction even if you practice online for hours.

“Data Analytics Online Quiz" is a virtual session designed to check your knowledge. This is a self-assessment tool, so you won’t be able to view questions or answers directly. This will bring randomly selected questions one by one, once you start a virtual session. You will be expected to provide answers within a predefined time limit. In the end, a summary of your virtual attempt will be shown.

Who can join us?

  • Want to become a Data Analyst
  • Aspiring to become Machine Learning Engineer
  • Want to be a Data Visualization Analyst
  • Looking for the Data Analytics interview questions and answers
  • Want to pass a relevant Freelance test, IT exam, or Pre-Employment assessment.
Free Sample Questions for Data Analytics

What will be the output of the following R code?

c(4,7,TRUE,3+7i) -> v1

c(9,6,FALSE,3+7i) ->> v2



[114+01 4+1i 7+01 3+7i

[1] 9+0i 9+1i 6+0i 3+7i 


[1] 9101 6+0i 0+01 3+7i  

[1) 4+0i 7+7l1+1i 3+7i

[1] 9+Oi 9+1i 6+6i 3+7i


[119+9i 6+6i1+1i 3+7i



[1] 9101 6+0i 0+01 3+7i  

A user wants to read and print the contents of a CSV file named myexample-csv that is present in his current working directory. Which of the following is the correct syntax of the command that should be executed by him to accomplish this task?

data <- read(myexample.csv)


data <- read.f‌ile(”myexample.csv")

data <- read.csv("myexample.csv")

data <~


data <- read.csv("myexample.csv")