stats::stdev
-- the standard
deviationstats::stdev
(data)
returns the standard
deviation of the data.
stats::stdev(x1, x2, .. <, Sample>)
stats::stdev([x1, x2, ..] <, Sample>)
stats::stdev(s <, c> <, Sample>)
x1, x2, .. |
- | the statistical data: arithmetical expressions. |
s |
- | a sample of domain type stats::sample . |
c |
- | an integer representing a column index of the sample
s . This column provides the data x1 ,
x2 etc. |
Sample |
- | with this option the given data are regarded as a ``sample'', not as a full population. |
an arithmetical expression.
stats::a_quantil
,
stats::geometric
,
stats::harmonic
,
stats::mean
, stats::median
, stats::modal
, stats::quadratic
, stats::variance
c
is optional, if the data are given
by a stats::sample
object containing only one non-string column. Cf. example 3.We calculate the standard deviation of three values:
>> stats::stdev(2, 3, 5)
1/2 14 ----- 3
Alternatively, the data may be passed as a list:
>> stats::stdev([2, 3, 5])
1/2 14 ----- 3
We create a sample:
>> stats::sample([[a1, b1, c1], [a2, b2, c2]])
a1 b1 c1 a2 b2 c2
The standard deviation of the second column is:
>> expand(stats::stdev(%, 2))
/ 2 2 \1/2 | b1 b1 b2 b2 | | --- - ----- + --- | \ 4 2 4 /
We create a sample consisting of one string column and one non-string column:
>> stats::sample([["1996", 1242], ["1997", 1353], ["1998", 1142]])
"1996" 1242 "1997" 1353 "1998" 1142
We compute the standard deviation of the second column. In this case this column does not have to be specified, since it is the only non-string column:
>> float(stats::stdev(%))
86.17939945
We repeat the computation with the option Sample:
>> float(stats::stdev(%2, Sample))
105.5477775
stats::sample
.