Logistic regression analysis in R for manuscript writing, Learn descriptive analysis, logistic regression, Poisson regression, linear regression, and manuscript-style result inte.
Course Description
This short hands-on course is designed for students, researchers, and beginners who want to learn practical regression analysis in R for manuscript-style reporting. Instead of memorizing theory, you will learn by doing a real data analysis project step by step in RStudio.
You will start with the basics, including opening RStudio, loading R packages, importing Excel data, selecting variables, dropping unnecessary variables, defining factor variables, and adding clear variable labels. Then, you will create descriptive and inferential summary tables, format mean ± SD and n (%), set decimal places, add p-values, finalize tables, and export results to Microsoft Word.
The course is organized around three practical research objectives. First, you will assess the association between sugar consumption and heart disease using logistic regression and odds ratio. Second, you will estimate the effect of sugar consumption on heart disease using Poisson regression and risk ratio. Third, you will assess the effect of sugar consumption on BMI using linear regression and mean difference.
By the end of this course, you will be able to prepare data, run regression models, create publication-ready tables, interpret odds ratios, risk ratios, regression coefficients, confidence intervals, and p-values, and write clear results for manuscript-style reporting. This course is simple, practical, and focused on real research data analysis skills.
Who this course is for:
- Students, researchers, and beginners who want to learn logistic regression in R and prepare regression results for manuscript-style reporting.
