Abstract
Pop‐Inference is an educational tool designed to help teaching of hypothesis testing using populations. The application allows for the statistical comparison of demographic parameters among populations. Input demographic data are projection matrices or raw demographic data. Randomization tests are used to compare populations. The tests evaluate the hypothesis that demographic parameters differ among groups of individuals more that should be expected from random allocation of individuals to populations. Confidence intervals for demographic parameters are obtained using the bootstrap. Tests may be global or pairwise. In addition to tests on differences, one‐way life table response experiments (LTRE) are available for random and fixed factors. Planned (a priori) comparisons are possible. Power of comparison tests is evaluated by constructing the distribution of the test statistic when the null hypothesis is true and when it is false. The relationship between power and sample size is explored by evaluating differences among populations at increasing population sizes, while keeping vital rates constant.
Highlights
Pop-Inference is an application written in MATLAB (The MathWorks Inc., Natick, MA, USA) code that uses randomization tests and the bootstrap to compare population parameters extracted from two or more populations
Students are often puzzled by the possibility of comparing population parameters, such as the population growth rate, using one single observation of the parameter per population
For vectorial parameters in pairwise comparisons, the test statistic is where m is the number of stages if stable stage structure (SSS) or reproductive value (RV) are being compared among populations or the number of distinct individual histories, p1j and p2j are the proportions for stage or history j in populations 1 or 2
Summary
Pop-Inference is an application written in MATLAB (The MathWorks Inc., Natick, MA, USA) code that uses randomization tests and the bootstrap to compare population parameters extracted from two or more populations. If two populations do not have different composition of life histories, we cannot reject the hypothesis of a common origin of individuals. Pop-Inference tests the hypothesis that the observed differences between populations are beyond the expected differences from sets of individuals sampled at random from a single population.
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