beta

Power Analysis and the Probability of Errors

September 22, 2012 | Wesley

Power analysis is a very useful tool to estimate the statistical power from a study. It effectively allows a researcher to determine the needed sample size in order to obtained the required statistical power. Clients often ask (and rightfully so) what the sample size should be for a proposed project. ... [Read more...]

Association and concordance measures

September 12, 2012 | arthur charpentier

Following the course, in order to define assocation measures (from Kruskal (1958)) or concordance measures (from Scarsini (1984)), define a concordance function as follows: let be a random pair with copula , and with copula . Then define the so-... [Read more...]

MAT8886 the Dirichlet distribution

February 15, 2012 | arthur charpentier

In the course, still introducing some concept of dependent distributions, we will talk about the Dirichlet distribution (which is a distribution over the simplex of ). Let denote the Gamma distribution with density (on ) Let denote independent... [Read more...]

Visualizing Bayesian Updating

September 10, 2011 | bayesianbiologist

One of the most straightforward examples of how we use Bayes to update our beliefs as we acquire more information can be seen with a simple Bernoulli process. That is, a process which has only two  possible outcomes. Probably the most commonly thought of example is that of a coin ... [Read more...]

Design of Experiments – Power Calculations

November 18, 2009 | Ralph

Prior to conducting an experiment researchers will often undertake power calculations to determine the sample size required in their work to detect a meaningful scientific effect with sufficient power. In R there are functions to calculate either a minimum sample size for a specific power for a test or the ... [Read more...]

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)