descr {ufs} | R Documentation |
This function provides a number of descriptives about your data, similar to what SPSS's DESCRIPTIVES (often called with DESCR) does.
descr( x, digits = 4, errorOnFactor = FALSE, include = c("central tendency", "spread", "range", "distribution shape", "sample size"), maxModes = 1, t = FALSE, conf.level = 0.95, quantileType = 2 ) ## Default S3 method: descr( x, digits = 4, errorOnFactor = FALSE, include = c("central tendency", "spread", "range", "distribution shape", "sample size"), maxModes = 1, t = FALSE, conf.level = 0.95, quantileType = 2 ) ## S3 method for class 'descr' print( x, digits = attr(x, "digits"), t = attr(x, "transpose"), row.names = FALSE, ... ) ## S3 method for class 'descr' pander(x, headerPrefix = "", headerStyle = "**", ...) ## S3 method for class 'descr' as.data.frame(x, row.names = NULL, optional = FALSE, ...) ## S3 method for class 'data.frame' descr(x, ...)
x |
The vector for which to return descriptives. |
digits |
The number of digits to round the results to when showing them. |
errorOnFactor |
Whether to show an error when the vector is a factor, or just show the frequencies instead. |
include |
Which elements to include when showing the results. |
maxModes |
Maximum number of modes to display: displays "multi" if more than this number of modes if found. |
t |
Whether to transpose the dataframes when printing them to the screen (this is easier for users relying on screen readers). |
conf.level |
Confidence of confidence interval around the mean in the central tendency measures. |
quantileType |
The type of quantiles to be used to compute the
interquartile range (IQR). See |
row.names |
Whether to show row names ( |
... |
Additional arguments are passed to the default |
headerPrefix |
The prefix for the heading; can be used to insert
hashes ( |
headerStyle |
A string to insert before and after the heading (to make stuff bold or italic in Markdown). |
optional |
Provided for compatibility with the default |
Note that R (of course) has many similar functions, such as
summary
, psych::describe()
in the excellent
psych::psych package.
The Hartigans' Dip Test may be unfamiliar to users; it is a measure of uni-
vs. multidimensionality, computed by diptest::dip.test()
from the
dip.test
package. Depending on the sample size, values over
.025 can be seen as mildly indicative of multimodality, while values over
.05 probably warrant closer inspection (the p-value can be obtained using
diptest::dip.test()
; also see Table 1 of Hartigan & Hartigan (1985) for
an indication as to critical values).
A list of dataframes with the requested values.
Gjalt-Jorn Peters
Maintainer: Gjalt-Jorn Peters gjalt-jorn@userfriendlyscience.com
Hartigan, J. A.; Hartigan, P. M. The Dip Test of Unimodality. Ann. Statist. 13 (1985), no. 1, 70–84. doi:10.1214/aos/1176346577. https://projecteuclid.org/euclid.aos/1176346577.
descr(mtcars$mpg);