The axes should be long enough so that values and labels can be easily read, but not hugely dissimilar in length. Inferential statistics are used to draw inferences about a population from a sample - trying to reach conclusions that extend beyond the immediate data. These two are the only inferential techniques we will cover on this course. Although no real datasets follow the normal distribution exactly, many kinds of data follow a distribution that is approximately Gaussian. A normal distribution can be defined by 2 parameters, the mean and the standard deviation .
Binary variables are quite common in biological data.
The random variable X is the number of occurrences of the event in an interval. The interval can be time, distance, area, volume or some similar unit. This method can be used to model many events, e.g. the number of orchids in a field or the probability of your computer crashing. Statistical methods which depend on the parameters of populations or probability distributions and are referred to as parametric methods . These tests are only meaningful for continuous data which is sampled from a population with an underlying normal distribution or whose distribution can be rendered normal by mathematical transformation .