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Welcome to Biostatistics! This course comes from the Peoples-uni module prepared by Marija Noursis and is based on her e-book Basics of Biostatistics.

The course introduces you to the art and science of collecting, analyzing and interpreting data from medical and biological studies.  Anyone who strives to improve human health based on empirical evidence must understand how to draw conclusions about populations based on data obtained from samples.  

The module presents statistical concepts without invoking mathematical complexity. Instead, the emphasis is on intuitive, easy-to-grasp, explanations and lots of examples drawn from the medical literature.  Open-source statistical software is used for analyzing data sets. Examples focus on issues that confront many low and middle-income countries. Basic maths and curiosity about the scientific method are the only prerequisites.

Upon completion of the module, you should be able to more confidently read the results sections of medical journals and to perform and interpret the results from frequently used statistical procedures. 

Getting started

Course Structure and Expectations: The main reference for the course is the e-book Basics of Biostatistics, by Marija Norusis, which you can download by clicking here. 

The course is structured into five topics.  For each topic, we will direct you to the reading resources that have been prepared to help you meet the course competencies. The basis of learning is to read these resources, and reflect on them.  In some cases, there are quizzes after the topic to allow you to self-assess your learning.  It is expected that you read all core resources and contribute to all reflections in order to make the most of these learning opportunities.

For students who wish to explore more advanced topics, there is additional material that covers models for survival data, multiple regression and logistic regression.

The topics are:

1. Describing and Summarizing Data

2. Evaluating Results from Samples

3. Basics of Hypothesis Testing

4. Testing Hypotheses about Counts

5. Correlation and Regression

Statistical software plays an important role in data analysis since almost all analyses are conducted using a computer.  In this course we make limited use of some easy-to-use open-source software since we can't provide you with expensive proprietary software and time is too limited to teach R, which is a very powerful open-source software. If you have access to SPSS, SAS, Stata or another statistical software package, and know how to use it, then feel free to utilise it instead of the open-source applications suggested in the topic questions.