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R for Researchers: From Basics to Advanced Analysis

Last updated on November 12, 2024 9:15 am
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Description

What you’ll learn

  • Develop practical skills in data manipulation, importing, and exporting using R.
  • Master descriptive statistics, correlations, ANOVA, and t-tests for research analysis.
  • Create basic, advanced, and animated graphs with R for insightful data visualization.
  • Enhance your creativity in data processing and statistical analysis in scientific research.
  • Gain proficiency in using R for comprehensive research projects and reporting.

Are you ready to elevate your research with the power of R programming? This course is designed to take you from the fundamentals to advanced techniques, all while applying real-world examples from diverse research fields.

With over 12 years of experience in programming and scientific research, I will guide you through essential skills that will transform the way you approach data analysis, statistics, and visualization. You’ll learn how to manipulate, import, and export data, conduct robust statistical analyses including correlations, ANOVA, and t-tests, and create both basic and advanced graphs using R programming.

Throughout the course, you’ll gain hands-on experience with RStudio, mastering everything from data handling to crafting dynamic visualizations. Unlike traditional software like SPSS and Excel, R offers endless possibilities for customization and creativity in your research.

By the end of this course, you’ll be able to:

  1. Process and analyze data creatively using R for research.

  2. Manipulate, import, and export data effectively.

  3. Perform comprehensive statistical analyses, including correlations, ANOVA, and t-tests.

  4. Create basic, advanced, and animated graphs with R.

  5. Utilize RStudio as your go-to tool for scientific research.

Join me, Assist. Prof. Azad Rasul, and unlock the full potential of R in your research journey. Let’s get started!

Who this course is for:

  • Researchers and students who are attempting to efficiently use R programming for their scientific research.

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