Statistical Methods Course
This course teaches practical statistical methods for survey data analysis using R and Python, covering data preprocessing, exploratory analysis, hypothesis testing, regression modeling, and effective communication of results.

4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This short, practical course guides you through importing, cleaning, and preprocessing survey data in R and Python, performing exploratory analyses, and running hypothesis tests and multiple linear regression with proper diagnostics. You will learn to handle missing values, outliers, and model assumptions, then clearly communicate results, limitations, and real-world implications to non-technical audiences with reproducible, high-quality reports.
Elevify advantages
Develop skills
- Data cleaning for surveys: fast import, validate, recode in R and Python.
- Exploratory stats: summarise, visualise, and stratify health data with rigour.
- Hypothesis testing: compare groups, run correlations, report effect sizes clearly.
- Regression modelling: build, diagnose, and interpret multiple linear regression.
- Results communication: craft clear, ethical, reproducible reports for stakeholders.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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