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This module covers key biostatistical concepts required to review and interpret findings published in the medical literature. Selected scientific publications are reviewed, discussed and criticised in terms of bias, uncertainty and scope. 

This session discusses key concepts in statistics. Classical and more recent exploratory data analysis techniques to efficiently summarise data and to detect outliers are presented. Statistical testing and decision-making in the presence of variation are also discussed.

Learn about key biostatistical concepts and efficient tools for summarising and plotting data as well as outlier detection. Demystify the statistical testing approach used to make decision in the presence of uncertainty: p-values, power, and so on. 

Efficient experiments must be large enough to detect meaningful scientific differences and maximize the use of available resources. Learn about sample size and power calculations.

Variation is present in every experiment. Learn about DOE techniques to control variation, and to maximise data quality. Commonly used experimental designs are discussed as well as the statistical data analysis tools.

An easy intro to key statistical concepts. Learn about data visualization and outlier detection. Demystify statistical significance testing. An excellent introductory module and a solid basis for all other modules.