This article provide a brief background about power and sample size analysis. Then, power and sample size analysis is computed for the Z test.

A very interesting paradigm in data analysis comes from the necessity to model data where it is difficult to think of a single global function to be capable to represent adequately the data.

We could see a spectrum of models going from the global statistical model, with a single function and associated probability distribution, to the decision tree fitting a set of constants at each leaf of the tree.

In the previous post we saw how much convenient could be **GenABEL** in the management of genotypic/phenotypic data.

We introduced the import of genotypic data from an Illumina format file:

`> convert.snp.illumina(inf = "gen.illu", out = "gen.raw", strand = "file")`

but what happens if you're analysing your data with **PLINK**, the open source toolset for GWAS?

This article gives a brief overview of the data.table package written by M. Dowle, T. Short, S. Lianoglou.

A data.table is an extension of a data.frame created to reduce the working time of the user in two ways:

- programming time
- compute time

Here is a little overview on **GenABEL** library developed by Yurii Aulchenko (**www.genabel.org/***)*.

GenABEL is a full-featured R library for dealing with Genome-Wide Association analysis of binary and quantitative traits.

Andrea Spanò, founder and partner at Quantide, held two seminars about Industrial Statistics at the University of Bergamo.

**Process Capability Analysis** and **Gage R&R** were topics of seminars.

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