Natural Resource BiometricsRandomnessFor many, the concept of "What is random?" is difficult to define. The term random indicates the lack of a repeatable, consistent, and testable patterns. The requirement is no bias and all possible locations have a known probability of being selected.
Why is this important in a class on sampling? The most recommended type of sampling by statisticians is random sampling. In statistics class, we have a collection of all individuals in a population. A random sample selects individuals from the population without a pattern or bias and all individuals have a known probability of being sampled. In this case the probability of being sampled is equal and dependent on the population size and the sample size. We will discuss this further in the topic sampling probabilities. So where do we get random number for our use? This question has several answers with issues with each. Let's look at some possibilities:
They most common way of testing a pseudo random number generator is to create 2 random number sequences and plot one sequence on the x and one on the y. Any diagonal alinement of the points indicates problems with the number generator. Because humans are very good at pattern recognition we tend to see pattern where none exist. There is a logical reason for this if you are a hunter or being hunted there is a greater penalty for not seeing a pattern that seeing a pattern that is not there. The out come of this is that the pattern we see in random numbers look like pattern but are not repeatable and detectable. The exercise in the video will demonstrate this idea.

Natural Resources Biometrics by David R. Larsen is licensed under a Creative Commons AttributionShareAlike 4.0 International License. Author: Dr. David R. Larsen Created: October 6, 2013 Last Updated: September 1, 2015 