Applied Statistics for Precision Medicine
About This Course
Learners should able to:
1) Explain principles of statistical modelling of data for precision medicine
2) Explain the challenges of analyzing high throughput datasets for precision medicine
3) Design high throughput experiments in precision medicine to minimize confounders and increase statistical power to detect differences
4) Evaluate data quality (batch effects, missing data, noise) and perform preprocessing where appropriate (batch correction, imputation, normalization)
5) Analyze high throughput data to find and evaluate differences in samples using appropriate statistical tools
What You'll Learn
Entry Requirements
Applicants must have a Bachelor’s degree and may be required to show
relevant work experience. Applicants with other qualifications and
experience may be considered on a case by case basis, subject to approval
by the school.Basic knowledge of R language