Understanding biochemistry: basic aspects of statistics for life sciences

If the biological world is one thing it is variable. As scientists we seek to measure, quantify and explain the causes of this variation. The approach we take to this is remarkably similar whether our research is exploring global temperature, blood pressure, cancer incidence or enzyme kinetics. This approach involves defining clear research questions and applying statistical methods to answer them robustly. This article will introduce a practical example that will be used throughout, specifically whether genetic variation can explain variation in coffee consumption. We assume little experience with statistics and walk through the statistical approach that biologists can use, firstly by describing our data with summary statistics and then by using statistical tests to help arrive at answers to our research question. A General Linear Model (GLM) approach will be used as this is what many common statistical tests are. We explore how to visualise and report results, while checking the assumptions of our analysis. The better we can understand and apply statistics to biological problems, the better we can communicate results and future research to others. The popular statistical programming language R will be used throughout.

Automated summary

This article introduces a statistical approach, using the General Linear Model (GLM), to study the relationship between genetic variation and variation in coffee consumption. By describing summary statistics and applying statistical tests, we can answer research questions and check analysis assumptions. The article emphasizes the importance of understanding and applying statistics to biological problems, as well as how to communicate research results and future research with others.