Statistical Analysis for In Vivo and In Vitro Scientists Course

This course organised by Responsible Research in Practice is designed to support life science researchers to select the most appropriate method of statistical analysis for their experimental design and to report results in a rigorous and reproducible way.

Session one will cover:

• Understanding, identifying, minimising variation and its impact.
• How the scientific question and experimental design influence the choice of statistical analysis method.
• What summary statistics are available and when to use them.
• Why and how to transform your data, plus strategies for dealing with outliers.
• The structure of a significance test using a two-sample t-test as an example.

Session two will cover:

• What measures of precision should be used and when, including SD Vs SEM plus confidence interval.
• Non-parametric statistical tests and other simple tests to compare more complex data sets.
• Basics of ANOVA and why it should often be used instead of multiple t-tests.

Session three will cover:

• What experimental designs and data features require an extension to statistical analysis methods such as ANOVA and how to incorporate them.
• ANOVA for randomised block designs and factorial treatment structures.
• Analysis of Covariance, ANCOVA Vs Change from Baseline.
• Assumptions of ANOVA and ANCOVA.

For more information visit the course page.