18 Questions
In which industries is R commonly used for data analysis and visualization?
Finance, marketing, healthcare, and retail
What is one of the main benefits of R's integration into business intelligence platforms?
Improved decision-making and reporting
What is a characteristic of R's open-source community?
Thousands of packages contributed by users worldwide
Why is R widely used in educational settings?
For teaching statistics, data analysis, and programming
What is one of R's strengths in data visualization?
Ability to create a wide variety of plots and charts
What is a key application of R in data science?
Predictive modeling, clustering, classification, and text mining
What is the primary use of R programming language and software environment?
Statistical computing and graphics
What was the primary driver of the development of R language?
Need for a flexible and extensible tool for statistical computing and graphics
Where did the development of R language originate?
University of Auckland, New Zealand
What was the influence on the development of R language?
S programming language
What is one of the industries where R is now widely used?
All of the above
What is the status of R language?
Open-source project
What is a key factor contributing to the widespread adoption of R?
Its open-source nature
Which of the following tasks is NOT a use case of R?
Network security analysis
What is a characteristic of R that makes it well-suited for data visualization?
Its powerful graphical capabilities for creating a wide range of plots and charts
Which of the following packages is commonly used for machine learning tasks in R?
caret
What is a benefit of using R for statistical analysis?
It provides a vast array of statistical functions
What is a common use case of R in data visualization?
Creating interactive visualizations
Test your knowledge of R programming, a popular language for data analysis, visualization, and science. Learn how R is used in industries such as finance and healthcare, and explore its capabilities for data exploration and insights.
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