Statistics for Non-Statisticians

The Statistics for Non-Statisticians programme is a three-course knowledge track that helps researchers and academics develop the statistical skills required for quantitative data analysis.

If you want to feel more confident in your approach to statistical analysis, look no further. The Statistics for Non-Statisticians knowledge track starts with the basics and builds to more advanced concepts step-by-step. All concepts are explained simply, through short, expert-led videos.

Throughout this self-paced programme, there are practical exercises and an interactive workbook that allow you to immediately practise all the methods you have learned.

The Statistics for Non-Statisticians knowledge track includes the following online courses:

1. Basic Statistical Concepts
2. Intermediate Statistical Concepts
3. Advanced Statistical Concepts

Basic Statistical Concepts starts with the absolute basics and identifies ways to present and describe measured data, perform a two-sample t-test, and interpret statistical significance.

Intermediate Statistical Concepts builds upon the first course and explains presentations and summaries of categorical data, ordinal data, and paired experimental designs and tests.

Advanced Statistical Concepts explores more advanced statistical concepts such as two-way analysis of variance (ANOVA), correlation, linear regression, logistic regression, analysis of covariance, multiple regression and dummy variables and confounding interpretations.

These online courses are particularly relevant for researchers and academics who have limited experience working with statistical concepts.

All courses are filled with compelling examples, interactive worksheets, and opportunities for reflection.

For this reason, we recommend you use a laptop or tablet if possible.

Dr. Philip Rowe

Dr. Philip Rowe is an author and former lecturer from Liverpool John Moores University, where he acted as academic faculty for more than 25 years. Throughout his career, he has taught clinical statistics, pharmacokinetics, and epidemiology to students and outside bodies (Professional and industrial).

He has analysed data in the fields of quantitative structure-activity relationships, pharmaceutical science, and pharmacy practice. He enjoys teaching mathematically based subjects to non-mathematicians in the biosciences in higher education and industry. His specialties include clinical statistics, pharmacokinetics, and epidemiology.