Our 1000+ R Programming questions and answers focuses on all areas of R Programming subject covering 100+ topics. These topics are chosen from a collection of most authoritative and best reference books on R Programming. One should spend 1 hour daily for 2-3 months to learn and assimilate this which will prepare anyone easily towards R Programming interviews, online tests, examinations and certifications.
– 1000+ Multiple Choice Questions & Answers in R Programming language with explanations
– Every MCQ set focuses on a specific topic in R Programming language
Who should Practice these R Programming Questions?
– Anyone wishing to sharpen their knowledge of R Programming language
– Anyone preparing for aptitude test in R Programming language
– Anyone preparing for interviews (campus/off-campus interviews, walk-in interview and company interviews)
– Anyone preparing for entrance examinations and other competitive examinations
– All – Experienced, Freshers and Students
Here’s list of Questions & Answers on R Programming language covering 100+ topics:
1. R – History, Overview and Getting Started
The section contains questions and answers on the basics and history of R-Programming language and console input and evaluation.
History of R
Overview of R
Console Input and Evaluation
2. R – Nuts and Bolts and Getting Data In and Out
The section contains questions and answers on data types and dataset reading in R-Programming.
3. R – Data Storage, Formats, Objects and Operations
The section contains questions and answers on text data formats, connecting interfaces, basics of dplyr, vector operations and subsets.
Textual Data Formats
Introduction to dplyr-1
Introduction to dplyr-2
4. R – Control Structures, Functions, Scoping Rules, Loop Functions and Debugging
The section contains questions and answers on control statements, date and time, functions, loops and scoping rules.
Dates and Times
5. R – Profiling, Simulation and Data Analysis
The section contains questions and answers on basics of simulation, ggplot, r-profiler, wrangling of data and exploratory data analysis.
Exploratory Data Analysis-1
Exploratory Data Analysis-2
6. R – Commands, Packages, Visualizing Data and Linear Regression
The section contains questions and answers on commands and packages, data visualization and linear regression and predictive analysis.
Wish you the best in your endeavor to learn and master R Programming!