Category Archives: statistics

## Binomial logistic regression models in R

In this post, we will look at a simple logistic binomial regression model in R. First, let's take a look at the following hypothetical data taken from [1]:   C = Yes C = No   Disease Disease   Yes No Yes No Exposure Yes 1200 600 300 400 No 400 100 600 400 It […]

## Chytrid fungus and logistic regression against temperature

Chytrid fungus refers to the fungus Batrachochytrium dendrobatidis (Bd). In amphibians, it causes a disease known as Chytridiomycosis. It is one of the worst diseases to strike out at multiple species of animals on the planet. This horrible disease degrades the skin, which in amphibians is a sensitive, permeable organ that is part of the […]

## Maximum likelihood, moments, and the mean of a Poisson

If we observe data coming from a distribution with known form but unknown parameters, estimating those parameters is our primary aim. If the distribution is uniform on $[0,\theta]$ with $\theta$ unknown, we already looked at two methods to estimate $\theta$ given $n$ i.i.d. observations $x_1,\dots,x_n$: Maximum likelihood, which maximizes the likelihood function and gives \$\max\{ […]

## A very quick tour of R

This post is a quick introduction to the R. I learnt R when I was an undergrad and I still use it from time to time. It was one of the first major programs I compiled from source as well. What is R? It is simply the best statistical computing environment in use today. Better […]

## P-values and goodness-of-fit normality testing

In statistical hypothesis testing, the computed p-value is the probability of getting a result "as extreme" as the given data under the null hypothesis. Here, "as extreme" means relative to a test-statistic, which has some distribution under the null hypothesis. In the natural sciences, an experiment is performed. A statistical test is used whose null […]