Course Introduction

Advanced Statistics and Data Analysis

Davide Risso

Class organization

  • 2 hrs of lecture in the morning (9:30 or 11:30)
  • 4 hrs of labs in the afternoon (14:30)

Office hours to be agreed over email.

Contacts

Davide Risso

Department of Statistical Sciences

via Cesare Battisti, 241

email: davide.risso@unipd.it

Class website: https://github.io/drisso/ASDA

My research interests

  • Statistical methodology: modeling of high-dimensional data, parametric and non-parametric regression, clus- tering, factor analysis and dimensionality reduction, multiple hypothesis testing, combining data from multiple sources (meta-analysis).
  • Omics data analysis: design and analysis of high-throughput gene expression experiments, analysis of single-cell and spatial transcriptomics.
  • Statistical software development: author of >10 Bioconductor packages, member of the Bioconductor Technical Advisory Board.

Program outline

Statistical topics

  1. (Everything is a) linear model
  2. Experimental deisgn
  3. The generalized linear model
  4. Likelihood estimation and inference
  5. Nonparametric methods: permutations and the bootstrap
  6. Multivariate analysis: PCA and more
  7. Advanced statistical models: random effects, Bayesian models, discrete states, …

Program outline

R topics

  1. How to make engaging and informative plots
  2. How to effectively “wrangle” data
  3. How to make your analysis reproducible
  4. Statistical modelling in practice

Suggested materials

  • There is no textbook.

  • Lecture slides and the companion website are the main resources.

  • In specific lectures I will give you additional materials, including suggested readings from books, journal articles, and more.

  • If you are looking for a comprehensive book that covers most of the topic taught in this course, check out Modern Statistics for Modern Biology

Exam

  • The exam will be in the computer lab, with R
  • It will consist of both practical matters (data exploration and analysis) as well as theoretical questions
  • The structure of the exam will be similar to the lab sessions

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