Free Download Learn Data Science & Biostatistics With R And Rstudio
Last updated 9/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 6.21 GB | Duration: 11h 33m
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 comprehensive RStudio course is designed to help beginners master the essentials of biostatistics and data science using R programming. Whether you're new to RStudio or an experienced data analyst, this course equips you with the skills to effectively analyze health and research data. Starting with a ggplot2 tutorial for data 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, including Linear, Logistic, Log-Binomial, and Poisson regression, essential in health research and epidemiology. You'll also explore how to use gtsummary to summarize complex datasets and generate publication-ready tables, ensuring your analysis meets statistical rigor. Throughout the course, you'll gain practical experience in interpreting critical measures like Odds 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 from R programming fundamentals to advanced concepts in data science and machine learning. As part of the journey, you will work hands-on with real health data, gaining experience with techniques like sample size calculations, chi-square tests, and advanced multivariate analysis methods. You will also learn how to address challenges such as missing data and multicollinearity in your research.Whether you're a beginner in R programming, a research assistant, or a public health professional, this course provides all the tools and knowledge needed to excel in data analysis. It is perfect for anyone looking to learn R for statistics and data science, and offers key insights for those interested in machine learning and data science bootcamps. By the end of the course, you will have mastered regression models, data visualization with ggplot2, and learned how to create professional data summaries with gtsummary.Join now to master R programming for biostatistics, advance your data science skills, and build a solid foundation for analyzing health and research datasets with RStudio.
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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