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In statistics, rankits of a set of data are the expected values of the order statistics of a sample from the standard normal distribution the same size as the data. They are primarily used in the normal probability plot, a graphical technique for normality testing.

Sample normal probability plot; horizontal axis coordinates are rankits.


This is perhaps most readily understood by means of an example. If an i.i.d. sample of six items is taken from a normally distributed population with expected value 0 and variance 1 (the standard normal distribution) and then sorted into increasing order, the expected values of the resulting order statistics are:

−1.2672,   −0.6418,   −0.2016,   0.2016,   0.6418,   1.2672.

Suppose the numbers in a data set are

65, 75, 16, 22, 43, 40.

Then one may sort these and line them up with the corresponding rankits; in order they are

16, 22, 40, 43, 65, 75,

which yields the points:

data point rankit
16 −1.2672
22 −0.6418
40 −0.2016
43 0.2016
65 0.6418
75 1.2672

These points are then plotted as the vertical and horizontal coordinates of a scatter plot.

Alternative method[edit]

Alternatively, rather than sort the data points, one may rank them, and rearrange the rankits accordingly. This yields the same pairs of numbers, but in a different order.


65, 75, 16, 22, 43, 40,

the corresponding ranks are:

5, 6, 1, 2, 4, 3,

i.e., the number appearing first is the 5th-smallest, the number appearing second is 6th-smallest, the number appearing third is smallest, the number appearing fourth is 2nd-smallest, etc. One rearranges the expected normal order statistics accordingly, getting the rankits of this data set:

data point rank rankit
65 5 0.6418
75 6 1.2672
16 1 −1.2672
22 2 −0.6418
43 4 0.2016
40 3 −0.2016

Rankit plot[edit]

A graph plotting the rankits on the horizontal axis and the data points on the vertical axis is called a rankit plot or a normal probability plot. Such a plot is necessarily nondecreasing. In large samples from a normally distributed population, such a plot will approximate a straight line. Substantial deviations from straightness are considered evidence against normality of the distribution.

Rankit plots are usually used to visually demonstrate whether data are from a specified probability distribution.

A rankit plot is a kind of Q-Q plot – it plots the order statistics (quantiles) of the sample against certain quantiles (the rankits) of the assumed normal distribution. Q-Q plots may use other quantiles for the normal distribution, however.


The rankit plot and the word rankit was introduced by the biologist and statistician Chester Ittner Bliss (1899–1979).

See also[edit]

  • Probit analysis developed by C. I. Bliss in 1934.

External links[edit]