Fonctions Statistiques

[ ] indicates optional parameters

BETA.INVERSE(probabilité; alpha; bêta; [A]; [B])
CENTILE(plage; k)
CENTREE.REDUITE(x; espérance; écart_type)
COEFFICIENT.ASYMETRIE(nombre1; [nombre2; ...])
COEFFICIENT.CORRELATION(plage1; plage2)
COEFFICIENT.DETERMINATION(y_range; x_range)
COVARIANCE(plage1; plage2)
CRITERE.LOI.BINOMIALE(tirages; probabilité_succès; alpha)
CROISSANCE(y_connus; [x_connus]; [x_nouveaux]; [constante])
DROITEREG(y_connus; [x_connus]; [constante]; [statistiques])
ECART.MOYEN(nombre1; [nombre2; ...])
ECARTYPE(nombre1; [nombre2; ...])
ECARTYPEP(nombre1; [nombre2; ...])
ERREUR.TYPE.XY(y_connus; x_connus)
FISHER(x)
FISHER.INVERSE(y)
FREQUENCE(tableau_données; matrice_intervalles)
GRANDE.VALEUR(plage; k)
INTERVALLE.CONFIANCE(alpha; écart_type; taille)
INVERSE.LOI.F(probabilité; degrés_liberté1; degrés_liberté2)
KHIDEUX.INVERSE(probabilité; degrés_liberté)
KURTOSIS(nombre1; [nombre2; ...])
LNGAMMA(x)
LOGREG(y_connus; [x_connus]; [constante]; [statistiques])
LOI.BETA(x; alpha; bêta; [A]; [B])
LOI.BINOMIALE(nombre_succès; tirages; probabilité_succès; cumulative)
LOI.BINOMIALE.NEG(nombre_f; nombre_s; probabilité_s)
LOI.EXPONENTIELLE(x; lambda; cumulative)
LOI.F(x; degrés_liberté1; degrés_liberté2)
LOI.GAMMA(x; alpha; bêta; cumulative)
LOI.GAMMA.INVERSE(probabilité; alpha; bêta)
LOI.HYPERGEOMETRIQUE(succès_échantillon; nombre_échantillon; succès_population; nombre_population)
LOI.KHIDEUX(x; degrés_liberté)
LOI.LOGNORMALE(x; espérance; écart_type)
LOI.LOGNORMALE.INVERSE(probabilité; espérance; écart_type)
LOI.NORMALE(x; espérance; écart_type; cumulative)
LOI.NORMALE.INVERSE(probabilité; espérance; écart_type)
LOI.NORMALE.STANDARD(z)
LOI.NORMALE.STANDARD.INVERSE(probabilité)
LOI.POISSON(x; espérance; cumulative)
LOI.STUDENT(x; degrés_liberté; uni/bilatéral)
LOI.STUDENT.INVERSE(probabilité; degrés_liberté)
LOI.WEIBULL(x; alpha; bêta; cumulative)
MAX(nombre1; [nombre2; ...])
MAXA(valeur1; [valeur2; ...])
MEDIANE(nombre1; [nombre2; ...])
MIN(nombre1; [nombre2; ...])
MINA(valeur1; [valeur2; ...])
MODE(nombre1; [nombre2; ...])
MOYENNE(nombre1; [nombre2; ...])
MOYENNEA(valeur1; [valeur2; ...])
MOYENNE.GEOMETRIQUE(nombre1; [nombre2; ...])
MOYENNE.HARMONIQUE(nombre1; [nombre2; ...])
MOYENNE.REDUITE(plage; pourcentage)
NB(valeur1; [valeur2; ...])
NBVAL(valeur1; [valeur2; ...])
ORDONNEE.ORIGINE(y_connus; x_connus)
PEARSON(plage1; plage2)
PENTE(y_connus; x_connus)
PERMUTATION(nombre; nombre_choisi)
PETITE.VALEUR(plage; k)
PREVISION(x; y_connus; x_connus)
PROBABILITE(plage_x; plage_probabilité; limite_inf; [limite_sup])
QUARTILE(plage; quart)
RANG(nombre; référence; [ordre])
RANG.POURCENTAGE(matrice; x; [précision])
SOMME.CARRES.ECARTS(nombre1; [nombre2; ...])
STDEVA(valeur1; [valeur2; ...])
STDEVPA(valeur1; [valeur2; ...])
TENDANCE(y_connus; [x_connus]; [x_nouveaux]; [constante])
TEST.F(plage1; plage2)
TEST.KHIDEUX(plage_réelle; plage_attendue)
TEST.STUDENT(matrice1; matrice2; uni/bilatéral; type)
TEST.Z(plage; x; [sigma])
VAR(nombre1; [nombre2; ...])
VAR.P(nombre1; [nombre2; ...])
VARA(valeur1; [valeur2; ...])
VARPA(valeur1; [valeur2; ...])


Fonctions Statistiques

BETA.INVERSE(probabilité; alpha; bêta; [A]; [B])

Returns the value associated with the specified cumulative beta distribution probability.

probabilitéThe cumulative beta distribution probability for which you want the value.
alphaThe alpha value.
bêtaThe beta value.
AThe lower limit. If this parameter is omitted it defaults to 0.
BThe upper limit. If this parameter is omitted it defaults to 1.


CENTILE(plage; k)

Returns the kth percentile of a set of values.

plageAn array or reference to cells containing the values.
kThe percentile value.


CENTREE.REDUITE(x; espérance; écart_type)

Returns the standardized value of x for the specified mean and standard deviation.

xThe value that you want to standardize.
espéranceThe mean of the values.
écart_typeThe standard deviation of the values.


COEFFICIENT.ASYMETRIE(nombre1; [nombre2; ...])

Returns the skewness of a set of numbers.

nombre1; ...The numbers of which you want the skewness.


COEFFICIENT.CORRELATION(plage1; plage2)

Returns the correlation coefficient of two ranges.

plage1The first range to be compared.
plage2The second range to be compared.


COEFFICIENT.DETERMINATION(y_range; x_range)

Returns the square of the Pearson correlation coefficient.

y_rangeThe first range to be compared.
x_rangeThe second range to be compared.


COVARIANCE(plage1; plage2)

Returns the covariance of two ranges.

plage1The first range to be compared.
plage2The second range to be compared.


CRITERE.LOI.BINOMIALE(tirages; probabilité_succès; alpha)

Returns the value at which the cumulative binomial distribution is greater than or equal to alpha.

tiragesThe total number of trials.
probabilité_succèsThe probability of a single trial being successful.
alphaThe value at which you want to evaluate the function.


CROISSANCE(y_connus; [x_connus]; [x_nouveaux]; [constante])

Returns the expected values of y for given x values for an exponential curve passing through a specified set of points.

y_connusThe y values that are already known.
x_connusThe x values that are already known. If this parameter is omitted it defaults to an array of values from 1 to the number of known ys.
x_nouveauxThe new x values for which y values are required. If this parameter is omitted it defaults to the known xs.
constanteSpecifies whether the line must pass through the origin. The possible values are:
FAUXThe intercept is forced to be 1.
VRAIThe intercept is calculated normally.
If this parameter is omitted it defaults to VRAI.


DROITEREG(y_connus; [x_connus]; [constante]; [statistiques])

Returns the coefficients for a straight line using multiple linear regression.

y_connusThe y values that are already known.
x_connusOne or more sets of x values corresponding to the known y values. If this parameter is omitted it defaults to an array of values from 1 to the number of known ys.
constanteSpecifies whether the line must pass through the origin. The possible values are:
FAUXThe line is forced to pass through the origin.
VRAIThe line is not forced to pass through the origin.
If this parameter is omitted it defaults to VRAI.
statistiquesSpecifies whether the additional statistics are returned in the rows below the coefficients. These are: the standard error values for the coefficients, the R2 coefficient, the standard error for the Y estimate, the F statistic, the degrees of freedom, the regression sum of squares and the residual sum of squares. The possible values are:
FAUXThe additional statistics are not returned.
VRAIThe additional statistics are returned.
If this parameter is omitted it defaults to FAUX.


ECART.MOYEN(nombre1; [nombre2; ...])

Returns the average of the differences of a set of numbers from their mean.

nombre1; ...The numbers of which you want the average deviation.


ECARTYPE(nombre1; [nombre2; ...])

Returns the standard deviation (based on a population sample) of a set of numbers.

nombre1; ...The numbers of which you want the standard deviation.


ECARTYPEP(nombre1; [nombre2; ...])

Returns the standard deviation (based on the entire population) of a set of numbers.

nombre1; ...The numbers of which you want the standard deviation.


ERREUR.TYPE.XY(y_connus; x_connus)

Returns the standard error of the y values of a line passing through a specified set of points.

y_connusThe y values that are already known.
x_connusThe x values that are already known.


FISHER(x)

Returns the Fisher transformation.

xThe value at which to evaluate the function.


FISHER.INVERSE(y)

Returns the inverse Fisher transformation.

yThe value at which to evaluate the function.


FREQUENCE(tableau_données; matrice_intervalles)

Returns the counts of items in specified numeric categories.

tableau_donnéesAn array or reference to a range of cells containing values to be counted.
matrice_intervallesAn array or reference to a range of cells containing the upper limits for each category.


GRANDE.VALEUR(plage; k)

Returns the kth largest number in a set of numbers.

plageAn array or reference to cells containing numbers of which you want the kth largest.
kThe rank of the number that you want.


INTERVALLE.CONFIANCE(alpha; écart_type; taille)

Returns the confidence interval for a population mean.

alphaThe significance level.
écart_typeThe population standard deviation.
tailleThe sample size.


INVERSE.LOI.F(probabilité; degrés_liberté1; degrés_liberté2)

Returns the value associated with the specified F distribution probability.

probabilitéThe probability for which you want the value.
degrés_liberté1The degrees of freedom of the first set.
degrés_liberté2The degrees of freedom of the second set.


KHIDEUX.INVERSE(probabilité; degrés_liberté)

Returns the value associated with the specified chi-squared distribution probability.

probabilitéThe probability for which you want the value.
degrés_libertéThe number of degrees of freedom.


KURTOSIS(nombre1; [nombre2; ...])

Returns the kurtosis of a set of numbers.

nombre1; ...The numbers of which you want the kurtosis.


LNGAMMA(x)

Returns the natural logarithm of the gamma function evaluated at x.

xThe value at which you want to evaluate the function.


LOGREG(y_connus; [x_connus]; [constante]; [statistiques])

Returns the coefficients for an exponential curve using multiple linear regression.

y_connusThe y values that are already known.
x_connusOne or more sets of x values corresponding to the known y values. If this parameter is omitted it defaults to an array of values from 1 to the number of known ys.
constanteSpecifies whether the line must pass through the origin. The possible values are:
FAUXThe intercept is forced to be 1.
VRAIThe intercept is calculated normally.
If this parameter is omitted it defaults to VRAI.
statistiquesSpecifies whether the additional statistics are returned in the rows below the coefficients. These are: the standard error values for the coefficients, the R2 coefficient, the standard error for the Y estimate, the F statistic, the degrees of freedom, the regression sum of squares and the residual sum of squares. The possible values are:
FAUXThe additional statistics are not returned.
VRAIThe additional statistics are returned.
If this parameter is omitted it defaults to FAUX.


LOI.BETA(x; alpha; bêta; [A]; [B])

Returns the cumulative beta distribution probability.

xThe value at which you want to evaluate the function.
alphaThe alpha value.
bêtaThe beta value.
AThe lower limit. If this parameter is omitted it defaults to 0.
BThe upper limit. If this parameter is omitted it defaults to 1.


LOI.BINOMIALE(nombre_succès; tirages; probabilité_succès; cumulative)

Returns the binomial distribution probability.

nombre_succèsThe number of trials that are successful.
tiragesThe total number of trials.
probabilité_succèsThe probability of a single trial being successful.
cumulativeSpecifies whether to return the cumulative probability or not. The possible values are:
FAUXReturn the value of the function.
VRAIReturn the integral of the function.


LOI.BINOMIALE.NEG(nombre_f; nombre_s; probabilité_s)

Returns the negative binomial distribution probability.

nombre_fThe number of trials that fail.
nombre_sThe threshold number of trials that are successful.
probabilité_sThe probability of a single trial being successful.


LOI.EXPONENTIELLE(x; lambda; cumulative)

Returns the exponential distribution probability.

xThe value at which you want to evaluate the function.
lambdaThe lambda value.
cumulativeSpecifies whether to return the cumulative probability or not. The possible values are:
FAUXReturn the value of the function.
VRAIReturn the integral of the function.


LOI.F(x; degrés_liberté1; degrés_liberté2)

Returns the F distribution probability.

xThe value at which you want to evaluate the function.
degrés_liberté1The degrees of freedom of the first set.
degrés_liberté2The degrees of freedom of the second set.


LOI.GAMMA(x; alpha; bêta; cumulative)

Returns the gamma distribution probability.

xThe value at which you want to evaluate the function.
alphaThe alpha value.
bêtaThe beta value.
cumulativeSpecifies whether to return the cumulative probability or not. The possible values are:
FAUXReturn the value of the function.
VRAIReturn the integral of the function.


LOI.GAMMA.INVERSE(probabilité; alpha; bêta)

Returns the value associated with the specified gamma distribution probability.

probabilitéThe probability for which you want the value.
alphaThe alpha value.
bêtaThe beta value.


LOI.HYPERGEOMETRIQUE(succès_échantillon; nombre_échantillon; succès_population; nombre_population)

Returns the hypergeometric distribution probability.

succès_échantillonThe number of sample trials that are successful.
nombre_échantillonThe total number of trials in the sample.
succès_populationThe number of population trials that are successful.
nombre_populationThe total number of trials in the population.


LOI.KHIDEUX(x; degrés_liberté)

Returns the chi-squared distribution probability.

xThe value at which you want to evaluate the function.
degrés_libertéThe number of degrees of freedom.


LOI.LOGNORMALE(x; espérance; écart_type)

Returns the cumulative lognormal distribution probability.

xThe value at which you want to evaluate the function.
espéranceThe mean of the natural logarithms of the values.
écart_typeThe standard deviation of the natural logarithms of the values.


LOI.LOGNORMALE.INVERSE(probabilité; espérance; écart_type)

Returns the value associated with the specified cumulative lognormal distribution probability.

probabilitéThe probability for which you want the value.
espéranceThe mean of the natural logarithms of the values.
écart_typeThe standard deviation of the natural logarithms of the values.


LOI.NORMALE(x; espérance; écart_type; cumulative)

Returns the normal distribution probability.

xThe value at which you want to evaluate the function.
espéranceThe mean of the values.
écart_typeThe standard deviation of the values.
cumulativeSpecifies whether to return the cumulative probability or not. The possible values are:
FAUXReturn the value of the function.
VRAIReturn the integral of the function.


LOI.NORMALE.INVERSE(probabilité; espérance; écart_type)

Returns the value associated with the specified cumulative normal distribution probability.

probabilitéThe probability for which you want the value.
espéranceThe mean of the values.
écart_typeThe standard deviation of the values.


LOI.NORMALE.STANDARD(z)

Returns the cumulative standard normal distribution probability.

zThe value at which you want to evaluate the function.


LOI.NORMALE.STANDARD.INVERSE(probabilité)

Returns the value associated with the specified cumulative standard normal distribution probability.

probabilitéThe probability for which you want the value.


LOI.POISSON(x; espérance; cumulative)

Returns the Poisson distribution probability.

xThe value at which you want to evaluate the function.
espéranceThe mean of the values.
cumulativeSpecifies whether to return the cumulative probability or not. The possible values are:
FAUXReturn the value of the function.
VRAIReturn the integral of the function.


LOI.STUDENT(x; degrés_liberté; uni/bilatéral)

Returns the Student's T distribution probability.

xThe value at which you want to evaluate the function.
degrés_libertéThe degrees of freedom.
uni/bilatéralSpecifies the tails to include in the distribution. Should be 1 or 2.


LOI.STUDENT.INVERSE(probabilité; degrés_liberté)

Returns the value associated with the specified Student's T distribution probability.

probabilitéThe probability for which you want the value.
degrés_libertéThe degrees of freedom.


LOI.WEIBULL(x; alpha; bêta; cumulative)

Returns the Weibull distribution probability.

xThe value at which you want to evaluate the function.
alphaThe alpha value.
bêtaThe beta value.
cumulativeSpecifies whether to return the cumulative probability or not. The possible values are:
FAUXReturn the value of the function.
VRAIReturn the integral of the function.


MAX(nombre1; [nombre2; ...])

Returns the maximum of a set of numbers.

nombre1; ...The numbers of which you want the maximum.


MAXA(valeur1; [valeur2; ...])

Returns the maximum of a set of values.

valeur1; ...The values of which you want the maximum.


MEDIANE(nombre1; [nombre2; ...])

Returns the median of a set of numbers.

nombre1; ...The numbers of which you want the median.


MIN(nombre1; [nombre2; ...])

Returns the minimum of a set of numbers.

nombre1; ...The numbers of which you want the minimum.


MINA(valeur1; [valeur2; ...])

Returns the minimum of a set of values.

valeur1; ...The values of which you want the minimum.


MODE(nombre1; [nombre2; ...])

Returns the mode of a set of numbers.

nombre1; ...The numbers of which you want the mode.


MOYENNE(nombre1; [nombre2; ...])

Returns the average of a set of numbers.

nombre1; ...The numbers of which you want the average.


MOYENNEA(valeur1; [valeur2; ...])

Returns the average of a set of values.

valeur1; ...The values of which you want the average.


MOYENNE.GEOMETRIQUE(nombre1; [nombre2; ...])

Returns the geometric mean of a set of numbers.

nombre1; ...The numbers of which you want the geometric mean.


MOYENNE.HARMONIQUE(nombre1; [nombre2; ...])

Returns the harmonic mean of a set of numbers.

nombre1; ...The numbers of which you want the harmonic mean.


MOYENNE.REDUITE(plage; pourcentage)

Returns the mean of a set of numbers with the extreme values removed.

plageAn array or reference to cells containing the numbers.
pourcentageThe percentage of the numbers to exclude from the calculation.


NB(valeur1; [valeur2; ...])

Returns the count of numbers in a list.

valeur1; ...The items whose numbers are to be counted.


NBVAL(valeur1; [valeur2; ...])

Returns the count of values in a list.

valeur1; ...The items whose values are to be counted.


ORDONNEE.ORIGINE(y_connus; x_connus)

Returns the expected value of y when x is zero for a line passing though a specified set of points.

y_connusThe y values that are already known.
x_connusThe x values that are already known.


PEARSON(plage1; plage2)

Returns the Pearson correlation coefficient.

plage1The first range to be compared.
plage2The second range to be compared.


PENTE(y_connus; x_connus)

Returns the slope of a line passing through a specified set of points.

y_connusThe y values that are already known.
x_connusThe x values that are already known.


PERMUTATION(nombre; nombre_choisi)

Returns the number of permutations in which a number of items can be chosen from a total number.

nombreThe total number of items.
nombre_choisiThe number of items chosen.


PETITE.VALEUR(plage; k)

Returns the kth smallest number in a set of numbers.

plageAn array or reference to cells containing numbers of which you want the kth smallest.
kThe rank of the number that you want.


PREVISION(x; y_connus; x_connus)

Returns the expected value of y for a given x value for a line passing through a specified set of points.

xThe x value at which to evaluate the function.
y_connusThe y values that are already known.
x_connusThe x values that are already known.


PROBABILITE(plage_x; plage_probabilité; limite_inf; [limite_sup])

Returns the probability that numbers in a set are between the specified limits.

plage_xAn array or reference to cells containing the numbers.
plage_probabilitéAn array or reference to cells containing the probabilities associated with each number. These values must add up to 1.
limite_infThe lower limit of the test.
limite_supThe upper limit of the test. If this value is omitted it defaults to the value specified for the lower limit.


QUARTILE(plage; quart)

Returns the specified quartile of a set of numbers.

plageAn array or reference to cells containing the numbers.
quartSpecifies which quartile to return. The possible values are:
0Returns the minimum value.
1Returns the first quartile.
2Returns the second quartile.
3Returns the third quartile.
4Returns the maximum value.


RANG(nombre; référence; [ordre])

Returns the rank of a number in a set of numbers.

nombreThe number of which you want the rank.
référenceAn array or reference to cells containing the values.
ordreSpecifies whether the list is treated as being in ascending or descending order of value. The possible values are:
0The list is in descending order (the highest value has rank 1).
any other valueThe list is in ascending order (the lowest value has rank 1).
If this parameter is omitted it defaults to 0.


RANG.POURCENTAGE(matrice; x; [précision])

Returns the percentile of a value in a set of values.

matriceAn array or reference to cells containing the values.
xThe value of which you want the percentile.
précisionThe number of decimal places required in the result. If this parameter is omitted it defaults to 3.


SOMME.CARRES.ECARTS(nombre1; [nombre2; ...])

Returns the sum of the squares of the differences of a set of numbers from their mean.

nombre1; ...The numbers of which you want the squared deviations.


STDEVA(valeur1; [valeur2; ...])

Returns the standard deviation (based on a population sample) of a set of values.

valeur1; ...The values of which you want the standard deviation.


STDEVPA(valeur1; [valeur2; ...])

Returns the standard deviation (based on the entire population) of a set of values.

valeur1; ...The values of which you want the standard deviation.


TENDANCE(y_connus; [x_connus]; [x_nouveaux]; [constante])

Returns the expected values of y for given x values for a line passing through a specified set of points.

y_connusThe y values that are already known.
x_connusThe x values that are already known. If this parameter is omitted it defaults to an array of values from 1 to the number of known ys.
x_nouveauxThe new x values for which y values are required. If this parameter is omitted it defaults to the known xs.
constanteSpecifies whether the line must pass through the origin. The possible values are:
FAUXThe line is forced to pass through the origin.
VRAIThe line is not forced to pass through the origin.
If this parameter is omitted it defaults to VRAI.


TEST.F(plage1; plage2)

Returns the probability result of the F test.

plage1The first range to be compared.
plage2The second range to be compared.


TEST.KHIDEUX(plage_réelle; plage_attendue)

Returns the probability result of the chi-squared test.

plage_réelleAn array or reference to cells containing the empirical results.
plage_attendueAn array or reference to cells containing the theoretical results.


TEST.STUDENT(matrice1; matrice2; uni/bilatéral; type)

Returns the probability result of the Student's T test.

matrice1The first range to be compared.
matrice2The second range to be compared.
uni/bilatéralSpecifies the tails to include in the distribution. Should be 1 or 2.
typeSpecifies which type of test is required. The possible values are:
1Paired.
2Equal variance.
3Unequal variance.


TEST.Z(plage; x; [sigma])

Returns the probability result of the z test.

plageAn array or reference to cells containing the data against which x is to be tested.
xThe value to be tested.
sigmaThe population standard deviation. If this parameter is omitted it defaults to the sample standard deviation of the data.


VAR(nombre1; [nombre2; ...])

Returns the variance (based on a population sample) of a set of numbers.

nombre1; ...The numbers of which you want the variance.


VAR.P(nombre1; [nombre2; ...])

Returns the variance (based on the entire population) of a set of numbers.

nombre1; ...The numbers of which you want the variance.


VARA(valeur1; [valeur2; ...])

Returns the variance (based on a population sample) of a set of values.

valeur1; ...The values of which you want the variance.


VARPA(valeur1; [valeur2; ...])

Returns the variance (based on the entire population) of a set of values.

valeur1; ...The values of which you want the variance.