The conclusion when the p-value is less than the critical alpha. Smallest Effect Size of Interest: the smallest effect that is theoretically or practically meaningful The probability of rejecting the null hypothesis when it is false.Ī number between 0 and 1 where 0 indicates impossibility of the event and 1 indicates certainty 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)Ī value that describes a distribution, such as the mean or SDĪ distribution that models independent events happening over a unit of time When a test concludes there is an effect when there really is no effectĪ named section of code that can be reused.Ī symmetric distribution of data where values near the centre are most probable.Īn outcome that does not show an otherwise expected effect. When a test concludes there is no effect when there really is an effect Some measure of your data, such as the mean value, or the number of standard deviations the mean differs from a chance value. Revisiting the binomial distribution, notice the and on the graph. The difference between the effect in your data and the null effect (usually a chance value) table from categorical data, making a pie chart, calculating the expected value. Parameters showing how a set of vectors vary and are correlated.ĭata that can only take certain values, such as integers. The relationship two vectors have to each other. Two normally distributed vectors that have a specified correlation with each other.Ī 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. The distribution of data where each observation can have one of two outcomes, like success/failure, yes/no or head/tails. The false negative rate we accept for a statistical test. (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 9.6.1 Means, Variability, and Deviation Scores.1.6.2 Reproducible reports with R Markdown.

Binomial distribution histogram maker