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Data Analytics (with R)

Data Analytics (with R)

Free Practice Test

FREE
  • No. of Questions10
  • AccessImmediate
  • Access DurationLife Long Access
  • Exam DeliveryOnline
  • Test ModesPractice
  • TypeExam Format

Practice Exam

$12.99
  • No. of Questions129
  • AccessImmediate
  • Access DurationLife Long Access
  • Exam DeliveryOnline
  • Test ModesPractice, Exam
  • Last UpdatedNovember 2024

Online Course

-
  • Content TypeVideo
  • DeliveryOnline
  • AccessImmediate
  • Access DurationLife Long Access
  • No of videos-
  • No of hours-
Not Available

Data Analytics (with R) Practice Exam Questions


R analytics (or R programming language) is amongst the free, open-source software used by professionals for all kinds of data science, statistics, and visualization projects. R programming language is amongst the most powerful, versatile languages with the ability to be integrated into BI platforms like Sisense, to assist with handling business-critical data.


Course Outline

The Data Analytics (with R) Practice Exam covers topics including -

  • Module 1 - Introduction
  • Module 2 - Descriptive Statistical Measures
  • Module 3 - Probability Distributions
  • Module 4 - Sampling and Estimation
  • Module 5 - Statistical Inference
  • Module 6 - R Programming Language Introduction
  • Module 7- Reading Data from files
  • Module 8 - Probability Distributions
  • Module 9 - Statistical Models in R
  • Module 10 - R Graphics Facilities
  • Module 11 - R Data Import/Export


Exam Format and Information

Exam Name Data Analytics (with R) 
Exam Code -
Exam Duration 60 mins
Exam Format Multiple Choice and Multi-Response Questions
Exam Type Cloud Computing
Number of Questions 50 Questions
Eligibility/Pre-Requisite NIL
Exam Status Live
Exam Language English, Japanese, Chinese (Simplified), Korean
Pass Score 700 (on a scale of 1-1000)

Data Analytics (with R) FAQs

Exam has been built with the focus on - 

  • Module 1 - Introduction
  • Module 2 - Descriptive Statistical Measures
  • Module 3 - Probability Distributions
  • Module 4 - Sampling and Estimation
  • Module 5 - Statistical Inference
  • Module 6 - R Programming Language Introduction
  • Module 7- Reading Data from files
  • Module 8 - Probability Distributions
  • Module 9 - Statistical Models in R
  • Module 10 - R Graphics Facilities
  • Module 11 - R Data Import/Export
  • Data Scientist.
  • Data Engineer.
  • Data Analyst.
  • Machine Learning Engineer.
  • Data Journalist.
  • Database Admin.
  • Financial Analyst.
  • Business Analyst.

  • Microsoft Excel.
  • Critical Thinking
  • R or Python–Statistical Programming.
  • Data Visualization.
  • Presentation Skills.
  • Machine Learning.
  • SQL


R-Software is one of the most important as well as a popular programming tools that is used by almost every organisation. Data analysis professionals are the ones with all the basic knowledge of R. They are responsible for providing simulations, data analyses and data visualizations with the R package. These professionals are highly in demand by every sector to design and develop their technical architecture as well as for preparing scripts for proper data access and formulation.

  • Software engineers
  • Web developers
  • Programmers
  • Bachelor’s in science and CS

 

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