How To Use R Programming for Research

The How To Use R Programming for Research course is a comprehensive program that provides students with a strong foundation in the R programming language and its applications in research. The course covers essential topics such as data manipulation, data visualization, statistical analysis, and machine learning using R.

Students will also learn how to import and export data, create data frames, use R libraries, and write their own functions. The course also includes case studies and practical examples, allowing students to apply their knowledge to real-world research scenarios.

Learning for all. Online courses from $12.99

With this course, students will gain the skills necessary to use R programming for research and analysis, and gain a competitive edge in the field of data science and research.

How To Use R Programming for Research Course Description

Here is an improved course description for “Learn R Programming for research by doing!”:

Are you looking to enhance your research skills using R programming? Look no further! This tutorial is based on my experience of many years and tens of scientific research projects using R. Each video will introduce you to a new concept that you can apply immediately to your own research. The best part? You will learn through real examples from a variety of research fields.

This course will not only make you a proficient practitioner but will also allow you to be creative in data processing, statistics, and graph creation in scientific research. R programming offers limitless possibilities compared to software such as SPSS and Excel. You will learn data types, manipulation, import, and export techniques, as well as descriptive statistics, relationships, multi-correlation, ANOVA, and t-test. You will also become familiar with basic, advanced, and animated graphs, as well as functions, packages, directories, and other important features of R.

As an Assistant Professor of Remote Sensing at Soran University and GBD Collaborator at the University of Washington, with more than 12 years of experience in Python and R programming, Java Script, Big Data, Remote Sensing/GIS, Earth Observation, and Climate, I have published around 30 peer-reviewed papers.

By the end of the course, you will have the following skills:

Creative data processing, statistical analysis, and graph creation using R for research.
Ability to manipulate, import, and export data.
Proficiency in descriptive statistics, relationships, multi-correlation, ANOVA, and t-test using R for scientific research.
Proficiency in basic, advanced, and animated graphs using R codes.
Knowledge of how to use R Studio for scientific research.