Inference

This group of courses is focused on statistical inference and it is developed at both undergraduate (statistics and life Sciences) an master level (in statistics). For the master courses, advance knowledge in both statistics and R is required at the beginning of the courses (students are expected to be familiar with hypothesis testing and estimation, distrubution functions and basic concepts in probability).

• Sample size calculation using R (See Sample size).

This course presents methods for sample size calculation using R. The course is developed at a master level by Martin Otava. R code for all examples included in the course is available online. In addtion, slides and YouTube tutorials are avilable in the repositories of the course. The course contents:

  +  Power.
  +  Efect size.
  +  Visualization.
  +  Sample size calculation for normal distributed endpoints.
  +  Liner regression and ANOVA.
  +  Generelized linear models:
  +  Binary data.
  +  Poisson distribution.
  +  Survival analysis.
  +  Correlated data and Longitudinal data.

All theoretical topics are illustared using examples in R.

• Basic concept in statistical inference using R (I): single comparison(See Basic Inference(I)).

This course presents the basic concepts of hypothesis testing for single comparison. This is an online course which was developed by Marc Lavielle within his initiative statistics in action with R (http://sia.webpopix.org/). R code for all examples illustrated in the course is available online. In addition, slides and YouTube tutorials are available in the repositories of the course. This course can be used as an introductory course for the other course in this cluster and can serve as a introduction course at a master level or a regular course at an undergraduate level.

• Introductory Statistics for the Life and Biomedical Sciences(See Introductory Statistics).

This course was developed for undergraduate students in Biomedical and life science. The course cover the topics of probability, distribution of random variables, foundations of inference, simple and multiple regression and inference for categorical data. This is an online course which was developed by Julie Vu (UCL) and David Harrington (Harvard). Materails for the course (book, R programs and data) are available online (https://github.com/OI-Biostat).

• Concepts in statistical inference using R: A master level course that will be avilable by the end of 2018,