Learn Data Science & Biostatistics with R and RStudio

Data Science & Biostatistics with R Programming and RStudio: From Fundamentals to Advanced Statistical Modeling

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.

The topics are:

r programming, rstudio, r for data science, learn r, r for beginners, tidyverse, dplyr, ggplot2, data wrangling in r, data visualization in r, statistics with r, logistic regression r, linear regression r, anova in r, survival analysis r, time series in r, forecasting in r, biostatistics with r, epidemiology with r, public health r, gtsummary, sample size calculation r, machine learning in r, tidymodels, caret, random forest r, xgboost r, r markdown, quarto, shiny, shiny dashboard, plotly r, excel to r, sql with r, readxl, readr, janitor, reproducible research r, reports in r, research with r, business analytics r

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