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Statistik Funktionen

[ ] indicates optional parameters

Statistik Funktionen

ACHSENABSCHNITT(Y_Werte; X_Werte)

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

Y_Werte	The y values that are already known.
X_Werte	The x values that are already known.

ANZAHL(Wert1; [Wert2; ...])

Returns the count of numbers in a list.

Wert1; ...

The items whose numbers are to be counted.

ANZAHL2(Wert1; [Wert2; ...])

Returns the count of values in a list.

Wert1; ...

The items whose values are to be counted.

ANZAHLLEEREZELLEN(Bereich)

Returns the number of blank cells in a range.

Bereich

The reference of the cells you want to check.

BESTIMMTHEITSMASS(Y_Werte; X_Werte)

Returns the square of the Pearson correlation coefficient.

Y_Werte	The first range to be compared.
X_Werte	The second range to be compared.

BETAINV(Wahrsch; Alpha; Beta; [A]; [B])

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

Wahrsch	The cumulative beta distribution probability for which you want the value.
Alpha	The alpha value.
Beta	The beta value.
A	The lower limit. If this parameter is omitted it defaults to 0.
B	The upper limit. If this parameter is omitted it defaults to 1.

BETAVERT(x; Alpha; Beta; [A]; [B])

Returns the cumulative beta distribution probability.

x	The value at which you want to evaluate the function.
Alpha	The alpha value.
Beta	The beta value.
A	The lower limit. If this parameter is omitted it defaults to 0.
B	The upper limit. If this parameter is omitted it defaults to 1.

BINOMVERT(Zahl_Erfolge; Versuche; Erfolgswahrsch; Kumuliert)

Returns the binomial distribution probability.

Zahl_Erfolge

The number of trials that are successful.

Versuche

The total number of trials.

Erfolgswahrsch

The probability of a single trial being successful.

Kumuliert

Specifies whether to return the cumulative probability or not. The possible values are:

FALSCH	Return the value of the function.
WAHR	Return the integral of the function.

CHIINV(Wahrsch; Freiheitsgrade)

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

Wahrsch	The probability for which you want the value.
Freiheitsgrade	The number of degrees of freedom.

CHITEST(Beob_Meßwert; Erwart_Werte)

Returns the probability result of the chi-squared test.

Beob_Meßwert	An array or reference to cells containing the empirical results.
Erwart_Werte	An array or reference to cells containing the theoretical results.

CHIVERT(x; Freiheitsgrade)

Returns the chi-squared distribution probability.

x	The value at which you want to evaluate the function.
Freiheitsgrade	The number of degrees of freedom.

EXPONVERT(x; Lambda; Kumuliert)

Returns the exponential distribution probability.

The value at which you want to evaluate the function.

Lambda

The lambda value.

Kumuliert

Specifies whether to return the cumulative probability or not. The possible values are:

FALSCH	Return the value of the function.
WAHR	Return the integral of the function.

FINV(Wahrsch; Freiheitsgrade1; Freiheitsgrade2)

Returns the value associated with the specified F distribution probability.

Wahrsch;	The probability for which you want the value.
Freiheitsgrade1	The degrees of freedom of the first set.
Freiheitsgrade2	The degrees of freedom of the second set.

FISHER(x)

Returns the Fisher transformation.

x	The value at which to evaluate the function.

FISHERINV(y)

Returns the inverse Fisher transformation.

y	The value at which to evaluate the function.

FTEST(Matrix1; Matrix2)

Returns the probability result of the F test.

Matrix1	The first range to be compared.
Matrix2	The second range to be compared.

FVERT(x; Freiheitsgrade1; Freiheitsgrade2)

Returns the F distribution probability.

x	The value at which you want to evaluate the function.
Freiheitsgrade1	The degrees of freedom of the first set.
Freiheitsgrade2	The degrees of freedom of the second set.

GAMMAINV(Wahrsch; Alpha; Beta)

Returns the value associated with the specified gamma distribution probability.

Wahrsch	The probability for which you want the value.
Alpha	The alpha value.
Beta	The beta value.

GAMMALN(x)

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

x	The value at which you want to evaluate the function.

GAMMAVERT(x; Alpha; Beta; Kumuliert)

Returns the gamma distribution probability.

The value at which you want to evaluate the function.

Alpha

The alpha value.

Beta

The beta value.

Kumuliert

Specifies whether to return the cumulative probability or not. The possible values are:

FALSCH	Return the value of the function.
WAHR	Return the integral of the function.

GEOMITTEL(Zahl1; [Zahl2; ...])

Returns the geometric mean of a set of numbers.

Zahl1; ...

The numbers of which you want the geometric mean.

GESTUTZTMITTEL(Matrix; Prozenz)

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

Matrix	An array or reference to cells containing the numbers.
Prozenz	The percentage of the numbers to exclude from the calculation.

GTEST(Matrix; x; [Sigma])

Returns the probability result of the z test.

Matrix;	An array or reference to cells containing the data against which x is to be tested.
x	The value to be tested.
Sigma	The population standard deviation. If this parameter is omitted it defaults to the sample standard deviation of the data.

HARMITTEL(Zahl1; [Zahl2; ...])

Returns the harmonic mean of a set of numbers.

Zahl1; ...

The numbers of which you want the harmonic mean.

HYPGEOMVERT(Erfolge_S; Umfang_S; Erfolge_G; Umfang_G)

Returns the hypergeometric distribution probability.

Erfolge_S	The number of sample trials that are successful.
Umfang_S	The total number of trials in the sample.
Erfolge_G	The number of population trials that are successful.
Umfang_G	The total number of trials in the population.

HÄUFIGKEIT(Daten; Klassen)

Returns the counts of items in specified numeric categories.

Daten	An array or reference to a range of cells containing values to be counted.
Klassen	An array or reference to a range of cells containing the upper limits for each category.

KGRÖSSTE(Matrix; k)

Returns the k^th largest number in a set of numbers.

Matrix	An array or reference to cells containing numbers of which you want the k^th largest.
k	The rank of the number that you want.

KKLEINSTE(Matrix; k)

Returns the k^th smallest number in a set of numbers.

Matrix	An array or reference to cells containing numbers of which you want the k^th smallest.
k	The rank of the number that you want.

KONFIDENZ(Alpha; Standabwn; Umfang_S)

Returns the confidence interval for a population mean.

Alpha	The significance level.
Standabwn	The population standard deviation.
Umfang_S	The sample size.

KORREL(Matrix1; Matrix2)

Returns the correlation coefficient of two ranges.

Matrix1	The first range to be compared.
Matrix2	The second range to be compared.

KOVAR(Matrix1; Matrix2)

Returns the covariance of two ranges.

Matrix1	The first range to be compared.
Matrix2	The second range to be compared.

KRITBINOM(Versuche; Erfolgswahrsch; Alpha)

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

Versuche	The total number of trials.
Erfolgswahrsch	The probability of a single trial being successful.
Alpha	The value at which you want to evaluate the function.

KURT(Zahl1; [Zahl2; ...])

Returns the kurtosis of a set of numbers.

Zahl1; ...

The numbers of which you want the kurtosis.

LOGINV(Wahrsch; Mittelwert; Standabwn)

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

Wahrsch	The probability for which you want the value.
Mittelwert	The mean of the natural logarithms of the values.
Standabwn	The standard deviation of the natural logarithms of the values.

LOGNORMVERT(x; Mittelwert; Standabwn)

Returns the cumulative lognormal distribution probability.

x	The value at which you want to evaluate the function.
Mittelwert	The mean of the natural logarithms of the values.
Standabwn	The standard deviation of the natural logarithms of the values.

MAX(Zahl1; [Zahl2; ...])

Returns the maximum of a set of numbers.

Zahl1; ...

The numbers of which you want the maximum.

MAXA(Wert1; [Wert2; ...])

Returns the maximum of a set of values.

Wert1; ...

The values of which you want the maximum.

MEDIAN(Zahl1; [Zahl2; ...])

Returns the median of a set of numbers.

Zahl1; ...

The numbers of which you want the median.

MIN(Zahl1; [Zahl2; ...])

Returns the minimum of a set of numbers.

Zahl1; ...

The numbers of which you want the minimum.

MINA(Wert1; [Wert2; ...])

Returns the minimum of a set of values.

Wert1; ...

The values of which you want the minimum.

MITTELABW(Zahl1; [Zahl2; ...])

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

Zahl1; ...

The numbers of which you want the average deviation.

MITTELWERT(Zahl1; [Zahl2; ...])

Returns the average of a set of numbers.

Zahl1; ...

The numbers of which you want the average.

MITTELWERTA(Wert1; [Wert2; ...])

Returns the average of a set of values.

Wert1; ...

The values of which you want the average.

MODALWERT(Zahl1; [Zahl2; ...])

Returns the mode of a set of numbers.

Zahl1; ...

The numbers of which you want the mode.

NEGBINOMVERT(Zahl_Mißerfolge; Zahl_Erfolge; Erfolgswahrsch)

Returns the negative binomial distribution probability.

Zahl_Mißerfolge	The number of trials that fail.
Zahl_Erfolge	The threshold number of trials that are successful.
Erfolgswahrsch	The probability of a single trial being successful.

NORMINV(Wahrsch; Mittelwert; Standabwn)

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

Wahrsch	The probability for which you want the value.
Mittelwert	The mean of the values.
Standabwn	The standard deviation of the values.

NORMVERT(x; Mittelwert; Standabwn; Kumuliert)

Returns the normal distribution probability.

The value at which you want to evaluate the function.

Mittelwert

The mean of the values.

Standabwn

The standard deviation of the values.

Kumuliert

Specifies whether to return the cumulative probability or not. The possible values are:

FALSCH	Return the value of the function.
WAHR	Return the integral of the function.

PEARSON(Matrix1; Matrix2)

Returns the Pearson correlation coefficient.

Matrix1	The first range to be compared.
Matrix2	The second range to be compared.

POISSON(x; Mittelwert; Kumuliert)

Returns the Poisson distribution probability.

The value at which you want to evaluate the function.

Mittelwert

The mean of the values.

Kumuliert

Specifies whether to return the cumulative probability or not. The possible values are:

FALSCH	Return the value of the function.
WAHR	Return the integral of the function.

QUANTIL(Matrix; Alpha)

Returns the k^th percentile of a set of values.

Matrix	An array or reference to cells containing the values.
Alpha	The percentile value.

QUANTILSRANG(Matrix; x; [Genauigkeit])

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

Matrix	An array or reference to cells containing the values.
x	The value of which you want the percentile.
Genauigkeit	The number of decimal places required in the result. If this parameter is omitted it defaults to 3.

QUARTILE(Matrix; Quartil)

Returns the specified quartile of a set of numbers.

Matrix

An array or reference to cells containing the numbers.

Quartil

Specifies which quartile to return. The possible values are:

0	Returns the minimum value.
1	Returns the first quartile.
2	Returns the second quartile.
3	Returns the third quartile.
4	Returns the maximum value.

RANG(Zahl; Bezug; [Reihenfolge])

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

Zahl

The number of which you want the rank.

Bezug

An array or reference to cells containing the values.

Reihenfolge

Specifies whether the list is treated as being in ascending or descending order of value. The possible values are:

0	The list is in descending order (the highest value has rank 1).
any other value	The list is in ascending order (the lowest value has rank 1).

If this parameter is omitted it defaults to 0.

RGP(Y_Werte, [X_Werte], [Konstante], [Stats])

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

Y_Werte

The y values that are already known.

X_Werte

One 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.

Konstante

Specifies whether the line must pass through the origin. The possible values are:

FALSCH	The line is forced to pass through the origin.
WAHR	The line is not forced to pass through the origin.

If this parameter is omitted it defaults to WAHR.

Stats

Specifies 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:

FALSCH	The additional statistics are not returned.
WAHR	The additional statistics are returned.

If this parameter is omitted it defaults to FALSCH.

RKP(Y_Werte, [X_Werte], [Konstante], [Stats])

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

Y_Werte

The y values that are already known.

X_Werte

One 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.

Konstante

Specifies whether the line must pass through the origin. The possible values are:

FALSCH	The intercept is forced to be 1.
WAHR	The intercept is calculated normally.

If this parameter is omitted it defaults to WAHR.

Stats

FALSCH	The additional statistics are not returned.
WAHR	The additional statistics are returned.

If this parameter is omitted it defaults to FALSCH.

SCHIEFE(Zahl1; [Zahl2; ...])

Returns the skewness of a set of numbers.

Zahl1; ...

The numbers of which you want the skewness.

SCHÄTZER(x; Y_Werte; X_Werte)

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

x	The x value at which to evaluate the function.
Y_Werte	The y values that are already known.
X_Werte	The x values that are already known.

STABW(Zahl1; [Zahl2; ...])

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

Zahl1; ...

The numbers of which you want the standard deviation.

STABWA(Wert1; [Wert2; ...])

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

Wert1; ...

The values of which you want the standard deviation.

STABWN(Zahl1; [Zahl2; ...])

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

Zahl1; ...

The numbers of which you want the standard deviation.

STABWNA(Wert1; [Wert2; ...])

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

Wert1; ...

The values of which you want the standard deviation.

STANDARDISIERUNG(x; Mittelwert; Standabwn)

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

x	The value that you want to standardize.
mean	The mean of the values.
standard_dev	The standard deviation of the values.

STANDNORMINV(Wahrsch)

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

Wahrsch

The probability for which you want the value.

STANDNORMVERT(z)

Returns the cumulative standard normal distribution probability.

z	The value at which you want to evaluate the function.

STEIGUNG(Y_Werte; X_Werte)

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

Y_Werte	The y values that are already known.
X_Werte	The x values that are already known.

STFEHLERYX(Y_Werte; X_Werte)

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

Y_Werte	The y values that are already known.
X_Werte	The x values that are already known.

SUMQUADABW(Zahl1; [Zahl2; ...])

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

Zahl1; ...

The numbers of which you want the squared deviations.

TINV(Wahrsch; Freiheitsgrade)

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

Wahrsch	The probability for which you want the value.
Freiheitsgrade	The degrees of freedom.

TREND(Y_Werte; [X_Werte]; [Neue_x_Werte]; [Konstante])

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

Y_Werte

The y values that are already known.

X_Werte

The 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.

Neue_x_Werte

The new x values for which y values are required. If this parameter is omitted it defaults to the known xs.

Konstante

Specifies whether the line must pass through the origin. The possible values are:

FALSCH	The line is forced to pass through the origin.
WAHR	The line is not forced to pass through the origin.

If this parameter is omitted it defaults to WAHR.

TTEST(Matrix1; Matrix2; Seiten; Typ)

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

Matrix1

The first range to be compared.

Matrix2

The second range to be compared.

Seiten

Specifies the tails to include in the distribution. Should be 1 or 2.

Typ

Specifies which type of test is required. The possible values are:

1	Paired.
2	Equal variance.
3	Unequal variance.

TVERT(x; Freheitsgrade; Seiten)

Returns the Student's T distribution probability.

x	The value at which you want to evaluate the function.
Freheitsgrade	The degrees of freedom.
Seiten	Specifies the tails to include in the distribution. Should be 1 or 2.

VARIANZ(Zahl1; [Zahl2; ...])

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

Zahl1; ...

The numbers of which you want the variance.

VARIANZA(Wert1; [Wert2; ...])

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

Wert1; ...

The values of which you want the variance.

VARIANZEN(Zahl1; [Zahl2; ...])

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

Zahl1; ...

The numbers of which you want the variance.

VARIANZENA(Wert1; [Wert2; ...])

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

Wert1; ...

The values of which you want the variance.

VARIATION(Y_Werte; [X_Werte]; [Neue_x_Werte]; [Konstante])

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

Y_Werte

The y values that are already known.

X_Werte

The 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.

Neue_x_Werte

The new x values for which y values are required. If this parameter is omitted it defaults to the known xs.

Konstante

Specifies whether the line must pass through the origin. The possible values are:

FALSCH	The intercept is forced to be 1.
WAHR	The intercept is calculated normally.

If this parameter is omitted it defaults to WAHR.

VARIATIONEN(n; k)

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

n	The total number of items.
k	The number of items chosen.

WAHRSCHBEREICH(Beob_Werte; Beob_Wahrsch; Untergrenze; [Obergrenze])

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

Beob_Werte	An array or reference to cells containing the numbers.
Beob_Wahrsch	An array or reference to cells containing the probabilities associated with each number. These values must add up to 1.
Untergrenze	The lower limit of the test.
Obergrenze	The upper limit of the test. If this value is omitted it defaults to the value specified for the lower limit.

WEIBULL(x; Alpha; Beta; Kumuliert)

Returns the Weibull distribution probability.

The value at which you want to evaluate the function.

Alpha

The alpha value.

Beta

The beta value.

Kumuliert

Specifies whether to return the cumulative probability or not. The possible values are:

FALSCH	Return the value of the function.
WAHR	Return the integral of the function.

ZÄHLENWENN(Bereich; Suchkriterium)

Returns the number of cells in a specified range that meet the specified criteria.

Bereich	A reference to the cells you want to count.
Suchkriterium	A string containing a comparison expression.