Elements of statistics 5: experimental design
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

** Scientific topics: **Statistics and probability

Elements of statistics 5: experimental design
https://bioconductor.org/help/course-materials/2014/CSAMA2014/5_Friday/lectures/ExpDesign_Anders.pdf
https://tess.elixir-europe.org/materials/elements-of-statistics-5-experimental-design
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Simon Anders
Statistics and probability

Elements of statistics 4: regularisation & kernels
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

** Scientific topics: **Statistics and probability

Elements of statistics 4: regularisation & kernels
https://bioconductor.org/help/course-materials/2014/CSAMA2014/4_Thursday/lectures/140626-brixen-machinelearn-huber.pdf
https://tess.elixir-europe.org/materials/elements-of-statistics-4-regularisation-kernels
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Wolfgang Huber
Statistics and probability

Elements of statistics 3: Classification and clustering - basic concepts
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

** Scientific topics: **Statistics and probability

Elements of statistics 3: Classification and clustering - basic concepts
https://bioconductor.org/help/course-materials/2014/CSAMA2014/4_Thursday/lectures/thursClust.html
https://tess.elixir-europe.org/materials/elements-of-statistics-3-classification-and-clustering-basic-concepts
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Unknown
Statistics and probability

Elements of statistics 1: t-test and linear model
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

** Scientific topics: **Statistics and probability

Elements of statistics 1: t-test and linear model
https://bioconductor.org/help/course-materials/2014/CSAMA2014/1_Monday/lectures/140623-gentleman-statistics-intro.pdf
https://tess.elixir-europe.org/materials/elements-of-statistics-1-t-test-and-linear-model
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Robert Gentleman
Statistics and probability

Lecture: Clustering and classification
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

** Scientific topics: **Statistics and probability

Lecture: Clustering and classification
https://bioconductor.org/help/course-materials/2015/CSAMA2015/lect/L04-clusclass-carey.html
https://tess.elixir-europe.org/materials/lecture-clustering-and-classification
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Vincent Carey
Statistics and probability

Lecture: Hypothesis testing and multiple testing
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

** Scientific topics: **Statistics and probability

Lecture: Hypothesis testing and multiple testing
https://bioconductor.org/help/course-materials/2015/CSAMA2015/lect/L03-testing-huber.pdf
https://tess.elixir-europe.org/materials/lecture-hypothesis-testing-and-multiple-testing
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Wolfgang Huber
Statistics and probability

Introduction to Bayesian Inference using Stan with Applications to Cancer Genomics
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

** Scientific topics: **Statistics and probability

Introduction to Bayesian Inference using Stan with Applications to Cancer Genomics
https://bioconductor.org/help/course-materials/2016/BioC2016/ConcurrentWorkshops4/Buros/applied-survival-model.html
https://tess.elixir-europe.org/materials/introduction-to-bayesian-inference-using-stan-with-applications-to-cancer-genomics
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Jacqueline Buros
Statistics and probability

Independent Hypothesis Weighting
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

** Scientific topics: **Statistics and probability

Independent Hypothesis Weighting
https://bioconductor.org/help/course-materials/2016/CSAMA/lab-6-hypothesis-weighting/introduction_to_ihw.Rmd
https://tess.elixir-europe.org/materials/independent-hypothesis-weighting
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Wolfgang Huber
Statistics and probability

Meta-analysis
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

** Scientific topics: **Statistics and probability

Meta-analysis
https://bioconductor.org/help/course-materials/2016/CSAMA/lect-18-meta-analysis/Waldron_metaanalysis.pdf
https://tess.elixir-europe.org/materials/meta-analysis
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Levi Waldron
Statistics and probability

Resampling methods
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

** Scientific topics: **Statistics and probability

Resampling methods
https://bioconductor.org/help/course-materials/2016/CSAMA/lect-12-resampling/Waldron_CSAMA2016_resampling.pdf
https://tess.elixir-europe.org/materials/resampling-methods
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Levi Waldron
Statistics and probability

Robust statistics
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

** Scientific topics: **Statistics and probability

Robust statistics
https://bioconductor.org/help/course-materials/2016/CSAMA/lect-11-robust/robust.pdf
https://tess.elixir-europe.org/materials/robust-statistics
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Michael Love
Statistics and probability

Introduction to linear models
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

** Scientific topics: **Statistics and probability

Introduction to linear models
https://bioconductor.org/help/course-materials/2016/CSAMA/lect-04-linear-models/Waldron_linearmodels.pdf
https://tess.elixir-europe.org/materials/introduction-to-linear-models
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Levi Waldron
Statistics and probability

Multiple testing
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

** Scientific topics: **Statistics and probability

Multiple testing
https://bioconductor.org/help/course-materials/2016/CSAMA/lect-02+13-testing/160711-brixen-testing-huber.pdf
https://tess.elixir-europe.org/materials/hypothesis-testing-27ffb208-e582-48db-a8c0-ad22a87a1329
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Wolfgang Huber
Statistics and probability

Probabilistic programming with (R)Stan
Probabilistic models describe how the observed data was generated, and what structure the signal and noise from potentially multiple sources may have. Many classical statistical models are special cases of probabilistic models with special modeling assumptions. Probabilistic models can be...

** Scientific topics: **Statistics and probability

Probabilistic programming with (R)Stan
https://www.bits.vib.be/training-list/112-bits/training/upcoming-trainings/358-probabilistic-programming-with-r-stan
https://tess.elixir-europe.org/materials/probabilistic-programming-with-r-stan
Probabilistic models describe how the observed data was generated, and what structure the signal and noise from potentially multiple sources may have. Many classical statistical models are special cases of probabilistic models with special modeling assumptions. Probabilistic models can be implemented, improved, and critizised in a flexible, explicit and transparent manner, and the analysis can be supported with prior information about the data.
This 1-day course provides an introduction to Bayesian/probabilistic models. We will implement standard linear models based on the rstanarm package of the R statistical programming environment and readily available example data sets. The workshop is an ideal opportunity to familiarize yourself with the basic ideas in probabilistic modeling such as prior information, likelihood, model criticism and validation, as well as some of the available tools. At the end, you should be able to implement basic probabilistic models yourself, and understand their relative advantages and pitfalls compared to their classical alternatives.
Leo Lahti
Statistics and probability
Life Science Researchers
PhD students
beginner bioinformaticians
post-docs
2016-04-22

Statistical Analysis using SPSS
Statistics are an important part of most modern studies and being able to effectively use a statistics package can help you to understand your results. This course provides an introduction to statistics illustrated though the use of the friendly SPSS package.

** Scientific topics: **Statistics and probability

** Keywords: **Babraham Institute

Statistical Analysis using SPSS
http://www.bioinformatics.babraham.ac.uk/training.html#spss
https://tess.elixir-europe.org/materials/statistical-analysis-using-spss
Statistics are an important part of most modern studies and being able to effectively use a statistics package can help you to understand your results. This course provides an introduction to statistics illustrated though the use of the friendly SPSS package.
Anne Segonds-Pichon
Statistics and probability
Babraham Institute

Introduction to R: A software environment for statistical computing
R is a free software environment for statistical computing and graphics. It is widely used in scientific data analysis. R is a great tool for biologists, since it provides cutting edge statistical techniques, excellent graph and figure plotting capabilities and bioinformatics tools all in one...

** Scientific topics: **Software engineering, Statistics and probability

** Keywords: **John Innes Centre, JIC

Introduction to R: A software environment for statistical computing
http://training.scicomp.jic.ac.uk/docs/r_intro_course_book/index.html
https://tess.elixir-europe.org/materials/introduction-to-r-a-software-environment-for-statistical-computing
R is a free software environment for statistical computing and graphics. It is widely used in scientific data analysis. R is a great tool for biologists, since it provides cutting edge statistical techniques, excellent graph and figure plotting capabilities and bioinformatics tools all in one package.
The John Innes Centre
Software engineering
Statistics and probability
John Innes Centre, JIC
Any students, postdocs or RAs who have an interest in bioinformatics and who intend to carry out statistical analysis of their experimental data using R. This two day course is planned to be a very gentle introduction to the very basic concepts of R.

Statistics with R
The aim of this course is to teach you how to perform basic statistical analysis using R. First we review the foundations (sampling theory, discrete and continuous distributions), then we focus on classical hypothesis testing. This course will improve your generic statistics knowledge....

** Scientific topics: **Statistics and probability

** Keywords: **Biostatistics, R

Statistics with R
https://www.mygoblet.org/training-portal/materials/statistics-r
https://tess.elixir-europe.org/materials/statistics-with-r
The aim of this course is to teach you how to perform basic statistical analysis using R. First we review the foundations (sampling theory, discrete and continuous distributions), then we focus on classical hypothesis testing. This course will improve your generic statistics knowledge.
Topics:
Sampling theory: obtaining information about a population via sampling.
Sample characteristics (location, dispersion, skewness), estimation of the mean, standard error of the mean.
Discrete and continuous probability distributions. Central limit theorem.
Hypothesis testing. Basic principles, one- and two-sided testing, types of errors, power calculations.
"Cookbook of tests": location testing, normality, variance comparisons,
counting statistics, contingency tables, regression tests.
András Aszódi
Statistics and probability
Biostatistics, R
2016-04-21
2017-10-09

Prerequisite
No description available

** Scientific topics: **Statistics and probability

** Keywords: **Unix, Linux, R-programming, Statistics

Prerequisite
https://microasp.upsc.se/ngs_trainers/Materials/tree/master/Content/Prerequisite/README.md
https://tess.elixir-europe.org/materials/prerequisite
No description available
Statistics and probability
Unix, Linux, R-programming, Statistics