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Advanced Statistics for the Life Sciences – HarvardX- EDX

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Here we will cover the advanced techniques being used by data analysis experts in the life sciences. These methods are required to analyze some of the more complex datasets, such as those found in genomics.

We will cover several topics including statistical modeling, multiple test correction, clustering, prediction methods, factor analysis and empirical Bayes methods. We will also elaborate on the use of R markdown to conduct reproducible research.


  • Statistical modeling
  • Multiple testing
  • Distance and clustering
  • Prediction
  • Factor analysis (batch effects)
  • Empirical Bayes (hierarchical modeling)

Important Date

2 March 2015

Registration opens through 27 April 2015


4 Week

6 hours / week

Full time/Part time

Part time

  • 1x and PH525.2x or basic programming,
  • Intro to statistics,
  • Intro to linear algebra
  • Rafael Irizarry
  • Michael Love
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