Data Science and Analytics Test Assessment

Topics covered

Introduction to Data Science, Analytics with R & Tools, Data Manipulation using R, Exploratory Data Analysis, Introduction to Statistics, Regression Analysis, Machine Learning Techniques using R, Data Visualization.

  • MAQ (Multiple Answer Question)
  • MCQ (Multiple Choice Question)
  • Descriptive Question
  • White Board Simulator
  • Coding Simulator
  • Audio Question
  • Video Question
  • Case Study Question

Data Science test is used to effectively assess the skills of candidates before an interview. Data Science is an interdisciplinary field of processes and systems to extract knowledge or insights from data in various forms which includes data analysis fields such as statistics, machine learning, and predictive analysis. It is designed to check the analytics and data science methods. The test is created and validated by Subject Matter Experts. 

The Data Science Test contains questions on following topics: 

  • Introduction to Data Science

  • Analytics with R & Tools

  • Data Manipulation using R

  • Exploratory Data Analysis

  • Introduction to Statistics

  • Regression Analysis

  • Machine Learning Techniques using R

  • Data Visualization


Interview Mocha’s Data Science test has a unique set of questions. You can also create or ask us to create a customized test that includes questions that are specific to your job-requirement.

Our powerful reporting helps you to analyze section wise performance of candidate to gauge his strengths and weaknesses. Moreover, you can always use our candidate ranking tool to screen best performing candidate amongst others.

This pre-employment test is useful for hiring:
  • Data Science Engineer

Test details:

Data Science Test enables employers and recruiters to evaluate skills and job readiness of candidates. For this reason, the emphasis is laid upon evaluating the knowledge of applied skills gained through real work experience, rather than theoretical knowledge.

Data Science test may contain MCQ's (Multiple Choice Questions), MAQ's (Multiple Answer Questions), Fill in the Blank, Descriptive, Whiteboard Questions, Audio / Video Questions, True or False.

Duration: 20 minutes 
20 Application Questions


The combination of Application and Theory questions helps to evaluate Technical as well as practical Skills of Candidates.

Data Science and Analytics Test

Question #1 of 3

Suppose I want to extract the first column of each matrix in the list. How I can do that?

    • zapply(x, function(elt) { elt[,1] })

    • lapply(x, function(elt) { elt[,1] })

    • extract(x, function(elt) { elt[,1] })

Question #2 of 3

I need to save the plot to PDF file, what should I do?

    • Construct the plot on the screen device and then copy it to a PDF file with dev.copy2pdf()

    • Open the screen device with quartz(), construct the plot, and then close the device with dev.off().

    • Open the PostScript device with postscript(), construct the plot, then close the device with dev.copy2pdf().

    • None of the mentioned

Question #3 of 3

What does the summaryRprof() function do?

    • tabulates the R profiler output and calculates how much time is spent in the first function

    • tabulates the R profiler output and calculates how much time is spend in which function

    • tabulates the R profiler output and calculates how much time is spend in all functions

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24.00 Out of 40.00
Pass
60%
03
23 Minutes

Java EE

9/10

Hibernate

3/10

Oracle PL/SQL

7/10

Analytical Thinking

5/10

Note:If score<= 30% then its a Weakness. If score >=70% then its a Strength.

Strengths

Java EE, Oracle PL/SQL, Analytical Thinking

Weaknesses

Hibernate

Happy

It was a good test for me, the questions were on the latest technology of java on which I am currently working. It was a great experience. Thank you!

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