14.10 Statistical functions
Many statistical functions can operate on a range of cells or an array .
In those cases where a list is specified as the parameter the function can also take a comma-separated list of values.
A list may contain cell references and also ranges of cells as one (or more) of their elements.
AVEDEV (
list )
AVERAGEA (
list )
AVG (
list )
BETA (
a ,
b )
BETA.DIST (
x ,
alpha ,
beta
{, cumulative
{, lower_limit
{, upper_limit } } } )
BETA.INV (
probability ,
alpha ,
beta
{, lower_limit
{, upper_limit } } } )
BIN (
data ,
bins )
BINOM.DIST (
number of successes ,
number of trials ,
probability of success ,
cumulative )
BINOM.DIST.RANGE (
number of trials ,
probability of success ,
number of successes ,
{, s2 } )
BINOM.INV (
number of trials ,
probability of success ,
alpha )
CHISQ.DIST (
x ,
degrees of freedom
{, cumulative } )
CHISQ.DIST.RT (
x ,
degrees of freedom )
CHISQ.INV (
probability ,
degrees of freedom )
CHISQ.INV.RT (
probability ,
degrees of freedom )
CHISQ.TEST (
actual data ,
expected data )
COMBIN (
n ,
k )
COMBINA (
n ,
m )
CONFIDENCE.NORM (
alpha ,
standard deviation ,
sample size )
CONFIDENCE.T (
alpha ,
standard deviation ,
sample size )
CORREL (
x‑data ,
y‑data )
COUNT (
list )
COUNTA (
list )
COUNTBLANK (
range )
COVARIANCE.P (
x‑data ,
y‑data )
COVARIANCE.S (
x‑data ,
y‑data )
DEVSQ (
list )
EXPON.DIST (
x ,
lambda
{, cumulative } )
F.DIST (
x ,
degrees of freedom in the numerator ,
degrees of freedom in the denominator
{, cumulative } )
F.DIST.RT (
x ,
degrees of freedom in the numerator ,
degrees of freedom in the denominator )
F.INV (
probability ,
degrees of freedom in the numerator ,
degrees of freedom in the denominator )
F.INV.RT (
probability ,
degrees of freedom in the numerator ,
degrees of freedom in the denominator )
F.TEST (
data 1 ,
data 2 )
FISHER (
x )
FISHERINV (
x )
FORECAST (
x ,
y‑data ,
x‑data )
FREQUENCY (
data ,
bins )
GAMMA (
x )
GAMMA.DIST (
x ,
shape ,
scale
{, cumulative } )
GAMMA.INV (
probability ,
shape ,
scale )
GAMMALN (
x )
GEOMEAN (
list )
GRAND ( )
GROWTH (
logest-data ,
x‑data )
HARMEAN (
list )
HYPGEOM.DIST (
sample_successes ,
number_sample ,
population_successes ,
number_population
{, cumulative } )
INTERCEPT (
y‑data ,
x‑data )
KURT (
list )
LARGE (
data ,
k )
LINEST (
known-ys ,
known-xs )
LISTCOUNT (
data )
LOGEST (
known-ys ,
known-xs )
LOGNORM.DIST (
x ,
mean ,
standard deviation
{, cumulative } )
LOGNORM.INV (
probability ,
mean ,
standard deviation )
MAX (
list )
MAXA (
list )
MEDIAN (
list )
MIN (
list )
MINA (
list )
MODE.SNGL (
data )
NEGBINOM.DIST (
number of failures ,
threshold number of successes ,
probability of success
{, cumulative } )
NORM.DIST (
x ,
mean ,
standard deviation
{, cumulative } )
NORM.INV (
probability ,
mean ,
standard deviation )
NORM.S.DIST (
z
{, cumulative } )
NORM.S.INV (
probability )
PEARSON (
x‑data ,
y‑data )
PERCENTILE.EXC (
data ,
k )
PERCENTILE.INC (
data ,
k )
PERCENTRANK.EXC (
data ,
value ,
digits )
PERCENTRANK.INC (
data ,
value ,
digits )
PERMUT (
n ,
k )
PHI (
z )
POISSON.DIST (
x ,
lambda ,
cumulative )
PROB (
x range ,
associated probabilities ,
lower limit
{, upper limit } )
QUARTILE.EXC (
data ,
q )
QUARTILE.INC (
data ,
q )
RANK (
data )
RANK.EQ (
value :number,
data
{, order } )
RSQ (
x‑data ,
y‑data )
SKEW (
list )
SKEW.P (
list )
SLOPE (
y‑data ,
x‑data )
SMALL (
data ,
k )
SPEARMAN (
array_1 ,
array_2 )
STANDARDIZE (
x ,
mu ,
sigma )
STD (
list )
STDEVA (
list )
STDEVPA (
list )
STDP (
list )
STEYX (
y‑data ,
x‑data )
T.DIST (
x ,
degrees of freedom
{, cumulative } )
T.DIST.2T (
x ,
degrees of freedom )
T.DIST.RT (
x ,
degrees of freedom )
T.INV (
probability ,
degrees of freedom )
T.INV.2T (
probability ,
degrees of freedom )
T.TEST (
data 1 ,
data 2 ,
tails ,
type )
TREND (
linest-data ,
x‑data )
TRIMMEAN (
data ,
percent )
VAR (
list )
VARA (
list )
VARP (
list )
VARPA (
list )
WEIBULL.DIST (
x ,
shape ,
scale ,
cumulative )
Z.TEST (
data ,
hypothesised mean
{, standard deviation )