stats.default | R Documentation |
Values of type factor
, character
and logical
are
treated as categorical. For logicals, the two categories are given the
labels 'Yes' for TRUE
, and 'No' for FALSE
. Factor levels with
zero counts are retained.
stats.default(x, quantile.type = 7, ...)
x |
A vector or numeric, factor, character or logical values. |
quantile.type |
An integer from 1 to 9, passed as the |
... |
Further arguments (ignored). |
A list. For numeric x
, the list contains the numeric elements:
N
: the number of non-missing values
NMISS
: the number of missing values
SUM
: the sum of the non-missing values
MEAN
: the mean of the non-missing values
SD
: the standard deviation of the non-missing values
MIN
: the minimum of the non-missing values
MEDIAN
: the median of the non-missing values
CV
: the percent coefficient of variation of the non-missing values
GMEAN
: the geometric mean of the non-missing values if non-negative, or NA
GSD
: the geometric standard deviation of the non-missing values if non-negative, or NA
GCV
: the percent geometric coefficient of variation of the
non-missing values if non-negative, or NA
qXX
: various quantiles (percentiles) of the non-missing
values (q01: 1%, q02.5: 2.5%, q05: 5%, q10: 10%, q25: 25% (first
quartile), q33.3: 33.33333% (first tertile), q50: 50% (median, or second
quartile), q66.7: 66.66667% (second tertile), q75: 75% (third quartile),
q90: 90%, q95: 95%, q97.5: 97.5%, q99: 99%)
Q1
: the first quartile of the non-missing values (alias q25
)
Q2
: the second quartile of the non-missing values (alias q50
or Median
)
Q3
: the third quartile of the non-missing values (alias q75
)
IQR
: the inter-quartile range of the non-missing values (i.e., Q3 - Q1
)
T1
: the first tertile of the non-missing values (alias q33.3
)
T2
: the second tertile of the non-missing values (alias q66.7
)
If x
is categorical (i.e. factor, character or logical), the list
contains a sublist for each category, where each sublist contains the
numeric elements:
FREQ
: the frequency count
PCT
: the percent relative frequency, including NA in the denominator
PCTnoNA
: the percent relative frequency, excluding NA from the denominator
NMISS
: the number of missing values
x <- exp(rnorm(100, 1, 1)) stats.default(x) y <- factor(sample(0:1, 99, replace=TRUE), labels=c("Female", "Male")) y[1:10] <- NA stats.default(y) stats.default(is.na(y))
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