The Weibull distribution is exceptionally well-suited to clinical and biomedical research because its shape parameter \(k\) carries direct interpretive meaning: whether the hazard of an event is decreasing (\(k < 1\)), constant (\(k = 1\)), or increasing (\(k > 1\)) over time. Below are thr...
read more →The Weibull distribution is one of the most widely used distributions in reliability engineering, survival analysis, and failure-time modelling. Named after Swedish engineer Waloddi Weibull (1951), it is prized for its flexibility: by tuning just two parameters it can mimic an exponential, a norm...
read more →It is hard to quickly evaluate data in an everyday situation, but a nifty shortcut I saw on the R-bloggers aggregator can help.
read more →The hypergeometric distribution is used to solve the classic “balls in an urn” proble. Suppose one has 7 red balls and 3 white ball in an urn, and draws 2 balls. What is the probability that both balls are white?
read more →The binomial distribution is used when there are n (a fixed number) independent trials with two possible outcomes (“success” and “failure”) with a probability that is constant.
read more →The Poisson distribution is the workhorse for count data — the number of times something happens in a fixed interval of time, space, or volume. Named after French mathematician Siméon Denis Poisson (1781-1840), it appears everywhere: call-centre arrivals, radioactive decay counts, hospital admiss...
read more →Fisher’s exact test is used to compare counts and proportions between groups when small samples of nominal variable are available. It assumes that the individual observations are independent, and that the row and column totals are fixed, or “conditioned.”
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