Programming Language for Economics
Introduction to R
This training introduces you to the use of R, a powerful and flexible interactive environment for statistical computing and research. In this training, we will begin with a basic introduction to the R system. You will learn about where to download R, how to install R, and how to upgrade R packages. You will discover how easy it is to use R for data management, simulate and analyze data from linear regression and other statistical tests. R is available for Linux, MacOS, and Windows. Get equipped with the competencies to use R software to analyze various economics data.
Importance of R
R is open source and freely available. It is available for Windows, Mac, and Linux operating systems. It has an extensive and coherent set of tools for statistical analysis. Its extensive and highly flexible graphical facility is capable of producing publication-quality figures. R has an expanding set of freely available ‘packages’ to extend R’s capabilities in addition to an extensive support network with numerous online and freely available documents.
$395 (Fee covers training materials)
August 28, 29, and 31 2026 10 am - 12 pm MT
Expected Learning Outcomes
By the end of this training, you will be able to
analyze data with R using RStudio;
use the different features of RStudio;
record data into R;
recognize all the R syntax;
recognize covariates and all the mathematical/statistical operators in R;
describe different data types and data forms in R;
explain the structure of a function in the context of R and its usage;
identify various R packages and libraries;
examine data structures; and
model or formulate various forms.
Target Learners
This training program is designed for individuals or groups of people who work in clinical settings, academia, pharmaceutical industries, Government, corporations, nonprofit organizations, and organizations that work on biological data.
Learning Approach
Programs are delivered through live online interactive sessions with seasoned instructors having vast experiences in academia. Contents are well structured and manageable with self-paced learning activities and exercises. Our approach provides learners opportunities for hands-on practice, asking questions, investigating problems, and applying their knowledge to solve complex scenarios or real-world problems. In the end, learners develop deeper understanding, critical thinking, and problem-solving skills.
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Why this course
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