Learn Data Science & Biostatistics with R and RStudio

Data Science & Biostatistics with R Programming and RStudio: From Fundamentals to Advanced ggplot Visualizations

What you'll learn
- Apply ggplot2 to create professional, publication-quality graphs for biostatistical data
- Use gtsummary to generate clear, formatted regression tables for research reporting
- Perform and interpret Linear Regression for continuous outcomes
- Conduct Logistic Regression to estimate odds ratios for binary outcomes
- Apply Log-Binomial Regression to directly estimate risk ratios

Requirements
- Basic understanding of R is recommended.
- Familiarity with fundamental statistics concepts such as mean, median, proportion, and basic regression.
- A computer with R and RStudio installed.
- Willingness to learn intermediate-level data analysis, visualization, and regression techniques in R.

Description
This comprehensiveRStudiocourse is designed to help beginners master the essentials ofbiostatisticsanddata scienceusingR programming. Whether you're new toRStudioor an experienced data analyst, this course equips you with the skills to effectively analyze health and research data. Starting with aggplot2tutorial fordata visualization, you’ll learn to build stunning charts and graphs to present your findings clearly and professionally.

The course will then guide you through key statistical methods, includingLinear,Logistic,Log-Binomial, andPoisson regression, essential inhealth researchandepidemiology. You’ll also explore how to usegtsummaryto summarize complex datasets and generatepublication-ready tables, ensuring your analysis meets statistical rigor. Throughout the course, you’ll gain practical experience in interpreting critical measures likeOdds Ratios,Risk Ratios, and more, understanding the relationships between different variables in your data.

Ideal for students, researchers, and health professionals with a basic understanding of statistics, this course covers everything fromR programmingfundamentals to advanced concepts indata scienceandmachine learning. As part of the journey, you will work hands-on withreal health data, gaining experience with techniques likesample size calculations,chi-square tests, and advancedmultivariate analysismethods. You will also learn how to address challenges such asmissing dataandmulticollinearityin your research.

Whether you're a beginner inR programming, aresearch assistant, or apublic health professional, this course provides all the tools and knowledge needed to excel indata analysis. It is perfect for anyone looking to learnR for statistics and data science, and offers key insights for those interested inmachine learninganddata science bootcamps. By the end of the course, you will have masteredregression models,data visualizationwithggplot2, and learned how to createprofessional data summarieswithgtsummary.

Join now to masterR programmingforbiostatistics, advance yourdata scienceskills, and build a solid foundation for analyzing health and research datasets withRStudio.

Who this course is for:
- Students, researchers, and professionals in health sciences, public health, or related fields who want to improve their data analysis skills.
- Learners with basic knowledge of R or statistics who want to advance to intermediate-level techniques in data visualization, regression, and summary statistics.
- Anyone interested in applying R for real-world health research data analysis, including estimating risk ratios, odds ratios, and creating publication-ready graphs.
- Intermediate R users who want to learn how to use packages like ggplot2 and gtsummary effectively for reporting and presentation.
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