Parameters showing how a set of vectors vary and are correlated.
A false positive; When a test concludes there is an effect when there is really is no effect
A distribution that models independent events happening over a unit of time
A named section of code that can be reused.
A false negative; When a test concludes there is no effect when there is really is an effect
When a test concludes there is an effect when there really is no effect
The false negative rate we accept for a statistical test.
A number between 0 and 1 where 0 indicates impossibility of the event and 1 indicates certainty
Two normally distributed vectors that have a specified correlation with each other.
The probability of seeing an effect at least as extreme as what you have, if the real effect was the value you are testing against (e.g., a null effect)
A distribution where all numbers in the range have an equal probability of being sampled
The distribution of data where each observation can have one of two outcomes, like success/failure, yes/no or head/tails.
The relationship two vectors have to each other.
Data that can only take certain values, such as integers.
Null Hypothesis Signficance Testing
(stats) The cutoff value for making a decision to reject the null hypothesis; (graphics) A value between 0 and 1 used to control the levels of transparency in a plot
A type of interval estimate used to summarise a given statistic or measurement where a proportion of intervals calculated from the sample(s) will contain the true value of the statistic.
Smallest Effect Size of Interest: the smallest effect that is theoretically or practically meaningful
Some measure of your data, such as the mean value, or the number of standard deviations the mean differs from a chance value.
The probability of rejecting the null hypothesis when it is false.
The difference between the effect in your data and the null effect (usually a chance value)
When a test concludes there is no effect when there really is an effect
A quantity characterizing a population.
Generating data from summary parameters
Relating to a single variable.
An outcome that does not show an otherwise expected effect.
The conclusion when the p-value is less than the critical alpha.
When a test concludes there is an effect when there is really is an effect
A symmetric distribution of data where values near the centre are most probable.
The end!