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Statistical Analysis with R for Research

Workshop overview

Welcome to the Statistical Analysis with R for Research Workshop! This 1-day intensive program is designed to equip researchers, students, and professionals with essential R programming skills for statistical analysis. Whether you are new to R or looking to enhance your skills, this workshop offers a hands-on experience to help you confidently analyze and interpret data for research purposes.

Learning outcomes

During this workshop, participants will:

  • Understand the fundamentals of R programming.
  • Learn data manipulation techniques using R.
  • Perform descriptive and inferential statistical analyses.
  • Create effective visualizations for data interpretation.
  • Apply R in research-specific scenarios.

The workshop will involve practical exercises, real-world examples, and guidance from experienced instructors to ensure you walk away with practical, applicable knowledge.

Who should attend?

  • Undergraduate and graduate students conducting research.
  • Academicians and professionals working with data.
  • Individuals with an interest in learning R for data analysis.

No prior programming experience is required, but basic knowledge of statistics will be helpful.

Why join this workshop?

By participating in this workshop, you will not only gain valuable analytical skills but also expand your professional network and enhance your ability to make data-driven decisions in your research field.

What is R?

R is an open source language and environment for statistical computing, data mining, modeling, and data graphics. It provides a wide variety of statistical and graphical techniques such as linear and non-linear modeling, statistical tests, time series analysis, classification, and clustering.

Why R?

  • R is a programming and statistical language.
  • R is used for data Analysis and Visualization.
  • R is simple and easy to learn, read and write.
  • R is an example of a FLOSS (Free Libre and Open Source Software) where one can freely distribute copies of this software, read its source code, modify it, etc.

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