# exceptionalScore: exceptionalScore In userfriendlyscience: Quantitative Analysis Made Accessible

## Description

This function can be used to detect exceptionally high or low scores in a vector.

## Usage

 ```1 2``` ```exceptionalScore(x, prob = 0.025, both = TRUE, silent = FALSE, quantileCorrection = 1e-04, quantileType = 8) ```

## Arguments

 `x` Vector in which to detect exceptional scores. `prob` Probability that a score is exceptionally positive or negative; i.e. scores with a quartile lower than `prob` or higher than 1-`prob` are considered exceptional (if both is TRUE, at least). So, note that a `prob` of .025 means that if both=TRUE, the most exceptional 5% of the values is marked as such. `both` Whether to consider values exceptional if they're below `prob` as well as above 1-`prob`, or whether to only consider values exceptional if they're below `prob` is `prob` is < .5, or above `prob` if `prob` > .5. `silent` Can be used to suppress messages. `quantileCorrection` By how much to correct the computed quantiles; this is used because when a distribution is very right-skewed, the lowest quantile is the lowest value, which is then also the mode; without subtracting a correction, almost all values would be marked as 'exceptional'. `quantileType` The algorithm used to compute the quantiles; see `quantile`.

## Details

Note that of course, by definition, `prob` of `2*prob` percent of the values is exceptional, so it is usually not a wise idea to remove scores based on their 'exceptionalness'. Instead, use `exceptionalScores`, which calls this function, to see how often participants answered exceptionally, and remove them based on that.

## Value

A logical vector, indicating for each value in the supplied vector whether it is exceptional.

## Author(s)

Gjalt-Jorn Peters

Maintainer: Gjalt-Jorn Peters <gjalt-jorn@userfriendlyscience.com>

`quantile`, `exceptionalScores`
 `1` ```exceptionalScore(c(1,1,2,2,2,3,3,3,4,4,4,5,5,5,5,6,6,7,8,20), prob=.05); ```