Statistics
- ADTEST — Anderson-Darling Test of Normality
- AVEDEV — average of the absolute deviations of a data set
- AVERAGE — average of all the numeric values and cells
- AVERAGEA — average of all the values and cells
- BERNOULLI — probability mass function of a Bernoulli distribution
- BETA.DIST — cumulative distribution function of the beta distribution
- BETADIST — cumulative distribution function of the beta distribution
- BETAINV — inverse of the cumulative distribution function of the beta distribution
- BINOM.DIST.RANGE — probability of the binomial distribution over an interval
- BINOMDIST — probability mass or cumulative distribution function of the binomial distribution
- CAUCHY — probability density or cumulative distribution function of the Cauchy, Lorentz or Breit-Wigner distribution
- CHIDIST — survival function of the chi-squared distribution
- CHIINV — inverse of the survival function of the chi-squared distribution
- CHITEST — p value of the Goodness of Fit Test
- CONFIDENCE — margin of error of a confidence interval for the population mean
- CONFIDENCE.T — margin of error of a confidence interval for the population mean using the Student's t-distribution
- CORREL — Pearson correlation coefficient of two data sets
- COUNT — total number of integer or floating point arguments passed
- COUNTA — number of arguments passed not including empty cells
- COVAR — covariance of two data sets
- COVARIANCE.S — sample covariance of two data sets
- CRITBINOM — right-tailed critical value of the binomial distribution
- CRONBACH — Cronbach's alpha
- CVMTEST — Cramér-von Mises Test of Normality
- DEVSQ — sum of squares of deviations of a data set
- EXPONDIST — probability density or cumulative distribution function of the exponential distribution
- EXPPOWDIST — the probability density function of the Exponential Power distribution
- FDIST — survival function of the F distribution
- FINV — inverse of the survival function of the F distribution
- FISHER — Fisher transformation
- FISHERINV — inverse of the Fisher transformation
- FORECAST — estimates a future value according to existing values using simple linear regression
- FREQUENCY — frequency table
- FTEST — p-value for the two-tailed hypothesis test comparing the variances of two populations
- GAMMADIST — probability density or cumulative distribution function of the gamma distribution
- GAMMAINV — inverse of the cumulative gamma distribution
- GEOMDIST — probability mass or cumulative distribution function of the geometric distribution
- GEOMEAN — geometric mean
- GROWTH — exponential growth prediction
- HARMEAN — harmonic mean
- HYPGEOMDIST — probability mass or cumulative distribution function of the hypergeometric distribution
- INTERCEPT — the intercept of a linear regression line
- KURT — unbiased estimate of the kurtosis of a data set
- KURTP — population kurtosis of a data set
- LANDAU — approximate probability density function of the Landau distribution
- LAPLACE — probability density function of the Laplace distribution
- LARGE — k-th largest value in a data set
- LEVERAGE — calculate regression leverage
- LINEST — multiple linear regression coefficients and statistics
- LKSTEST — Lilliefors (Kolmogorov-Smirnov) Test of Normality
- LOGEST — exponential least square fit
- LOGFIT — logarithmic least square fit (using a trial and error method)
- LOGINV — inverse of the cumulative distribution function of the lognormal distribution
- LOGISTIC — probability density function of the logistic distribution
- LOGNORMDIST — cumulative distribution function of the lognormal distribution
- LOGREG — the logarithmic regression
- MAX — largest value, with negative numbers considered smaller than positive numbers
- MAXA — largest value, with negative numbers considered smaller than positive numbers
- MEDIAN — median of a data set
- MIN — smallest value, with negative numbers considered smaller than positive numbers
- MINA — smallest value, with negative numbers considered smaller than positive numbers
- MODE — first most common number in the dataset
- MODE.MULT — most common numbers in the dataset
- NEGBINOMDIST — probability mass function of the negative binomial distribution
- NORMDIST — probability density or cumulative distribution function of a normal distribution
- NORMINV — inverse of the cumulative distribution function of a normal distribution
- NORMSDIST — cumulative distribution function of the standard normal distribution
- NORMSINV — inverse of the cumulative distribution function of the standard normal distribution
- OWENT — Owen's T function
- PARETO — probability density function of the Pareto distribution
- PEARSON — Pearson correlation coefficient of the paired set of data
- PERCENTILE — determines the 100*k-th percentile of the given data points (Hyndman-Fan method 7: N-1 basis)
- PERCENTILE.EXC — determines the 100*k-th percentile of the given data points (Hyndman-Fan method 6: N+1 basis)
- PERCENTRANK — rank of a data point in a data set (Hyndman-Fan method 7: N-1 basis)
- PERCENTRANK.EXC — rank of a data point in a data set (Hyndman-Fan method 6: N+1 basis)
- PERMUT — number of k-permutations of a n-set
- PERMUTATIONA — the number of permutations of y objects chosen from x objects with repetition allowed
- POISSON — probability mass or cumulative distribution function of the Poisson distribution
- PROB — probability of an interval for a discrete (and finite) probability distribution
- QUARTILE — the k-th quartile of the data points (Hyndman-Fan method 7: N-1 basis)
- QUARTILE.EXC — the k-th quartile of the data points (Hyndman-Fan method 6: N+1 basis)
- R.DBETA — probability density function of the beta distribution
- R.DBINOM — probability density function of the binomial distribution
- R.DCAUCHY — probability density function of the Cauchy distribution
- R.DCHISQ — probability density function of the chi-square distribution
- R.DEXP — probability density function of the exponential distribution
- R.DF — probability density function of the F distribution
- R.DGAMMA — probability density function of the gamma distribution
- R.DGEOM — probability density function of the geometric distribution
- R.DGUMBEL — probability density function of the Gumbel distribution
- R.DHYPER — probability density function of the hypergeometric distribution
- R.DLNORM — probability density function of the log-normal distribution
- R.DNBINOM — probability density function of the negative binomial distribution
- R.DNORM — probability density function of the normal distribution
- R.DPOIS — probability density function of the Poisson distribution
- R.DRAYLEIGH — probability density function of the Rayleigh distribution
- R.DSNORM — probability density function of the skew-normal distribution
- R.DST — probability density function of the skew-t distribution
- R.DT — probability density function of the Student t distribution
- R.DWEIBULL — probability density function of the Weibull distribution
- R.PBETA — cumulative distribution function of the beta distribution
- R.PBINOM — cumulative distribution function of the binomial distribution
- R.PCAUCHY — cumulative distribution function of the Cauchy distribution
- R.PCHISQ — cumulative distribution function of the chi-square distribution
- R.PEXP — cumulative distribution function of the exponential distribution
- R.PF — cumulative distribution function of the F distribution
- R.PGAMMA — cumulative distribution function of the gamma distribution
- R.PGEOM — cumulative distribution function of the geometric distribution
- R.PGUMBEL — cumulative distribution function of the Gumbel distribution
- R.PHYPER — cumulative distribution function of the hypergeometric distribution
- R.PLNORM — cumulative distribution function of the log-normal distribution
- R.PNBINOM — cumulative distribution function of the negative binomial distribution
- R.PNORM — cumulative distribution function of the normal distribution
- R.PPOIS — cumulative distribution function of the Poisson distribution
- R.PRAYLEIGH — cumulative distribution function of the Rayleigh distribution
- R.PSNORM — cumulative distribution function of the skew-normal distribution
- R.PST — cumulative distribution function of the skew-t distribution
- R.PT — cumulative distribution function of the Student t distribution
- R.PTUKEY — cumulative distribution function of the Studentized range distribution
- R.PWEIBULL — cumulative distribution function of the Weibull distribution
- R.QBETA — probability quantile function of the beta distribution
- R.QBINOM — probability quantile function of the binomial distribution
- R.QCAUCHY — probability quantile function of the Cauchy distribution
- R.QCHISQ — probability quantile function of the chi-square distribution
- R.QEXP — probability quantile function of the exponential distribution
- R.QF — probability quantile function of the F distribution
- R.QGAMMA — probability quantile function of the gamma distribution
- R.QGEOM — probability quantile function of the geometric distribution
- R.QGUMBEL — probability quantile function of the Gumbel distribution
- R.QHYPER — probability quantile function of the hypergeometric distribution
- R.QLNORM — probability quantile function of the log-normal distribution
- R.QNBINOM — probability quantile function of the negative binomial distribution
- R.QNORM — probability quantile function of the normal distribution
- R.QPOIS — probability quantile function of the Poisson distribution
- R.QRAYLEIGH — probability quantile function of the Rayleigh distribution
- R.QSNORM — probability quantile function of the skew-normal distribution
- R.QST — probability quantile function of the skew-t distribution
- R.QT — probability quantile function of the Student t distribution
- R.QTUKEY — probability quantile function of the Studentized range distribution
- R.QWEIBULL — probability quantile function of the Weibull distribution
- RANK — rank of a number in a list of numbers
- RANK.AVG — rank of a number in a list of numbers
- RAYLEIGH — probability density function of the Rayleigh distribution
- RAYLEIGHTAIL — probability density function of the Rayleigh tail distribution
- RSQ — square of the Pearson correlation coefficient of the paired set of data
- SFTEST — Shapiro-Francia Test of Normality
- SKEW — unbiased estimate for skewness of a distribution
- SKEWP — population skewness of a data set
- SLOPE — the slope of a linear regression line
- SMALL — k-th smallest value in a data set
- SNORM.DIST.RANGE — probability of the standard normal distribution over an interval
- SSMEDIAN — median for grouped data
- STANDARDIZE — z-score of a value
- STDEV — sample standard deviation of the given sample
- STDEVA — sample standard deviation of the given sample
- STDEVP — population standard deviation of the given population
- STDEVPA — population standard deviation of an entire population
- STEYX — standard error of the predicted y-value in the regression
- SUBTOTAL — the subtotal of the given list of arguments
- TDIST — survival function of the Student t-distribution
- TINV — two tailed inverse of the Student t-distribution
- TREND — estimates future values of a given data set using a least squares approximation
- TRIMMEAN — mean of the interior of a data set
- TTEST — p-value for a hypothesis test comparing the means of two populations using the Student t-distribution
- VAR — sample variance of the given sample
- VARA — sample variance of the given sample
- VARP — variance of an entire population
- VARPA — variance of an entire population
- WEIBULL — probability density or cumulative distribution function of the Weibull distribution
- ZTEST — the probability of observing a sample mean as large as or larger than the mean of the given sample
ADTEST
Synopsis
ADTEST(x)
Arguments
x: array of sample values
Description
This function returns an array with the first row giving the p-value of the Anderson-Darling Test, the second row the test statistic of the test, and the third the number of observations in the sample.
Note
If there are less than 8 sample values, ADTEST returns #VALUE!
AVEDEV
Synopsis
AVEDEV(number1,number2,…)
Arguments
number1: first value
number2: second value
Microsoft Excel Compatibility
This function is Excel compatible.
See also
AVERAGE
Synopsis
AVERAGE(number1,number2,…)
Arguments
number1: first value
number2: second value
Microsoft Excel Compatibility
This function is Excel compatible.
AVERAGEA
Synopsis
AVERAGEA(number1,number2,…)
Arguments
number1: first value
number2: second value
Description
Numbers, text and logical values are included in the calculation too. If the cell contains text or the argument evaluates to FALSE, it is counted as value zero (0). If the argument evaluates to TRUE, it is counted as one (1). Note that empty cells are not counted.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
BERNOULLI
Synopsis
BERNOULLI(k,p)
Arguments
k: integer
p: probability of success
Note
If k != 0 and k != 1 this function returns a #NUM! error. If p < 0 or p > 1 this function returns a #NUM! error.
See also
BETA.DIST
Synopsis
BETA.DIST(x,alpha,beta,cumulative,a,b)
Arguments
x: number
alpha: scale parameter
beta: scale parameter
cumulative: whether to evaluate the density function or the cumulative distribution function
a: optional lower bound, defaults to 0
b: optional upper bound, defaults to 1
Note
If x < a or x > b this function returns a #NUM! error. If alpha <= 0 or beta <= 0, this function returns a #NUM! error. If a >= b this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
BETADIST
Synopsis
BETADIST(x,alpha,beta,a,b)
Arguments
x: number
alpha: scale parameter
beta: scale parameter
a: optional lower bound, defaults to 0
b: optional upper bound, defaults to 1
Note
If x < a or x > b this function returns a #NUM! error. If alpha <= 0 or beta <= 0, this function returns a #NUM! error. If a >= b this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
BETAINV
Synopsis
BETAINV(p,alpha,beta,a,b)
Arguments
p: probability
alpha: scale parameter
beta: scale parameter
a: optional lower bound, defaults to 0
b: optional upper bound, defaults to 1
Note
If p < 0 or p > 1 this function returns a #NUM! error. If alpha <= 0 or beta <= 0, this function returns a #NUM! error. If a >= b this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
BINOM.DIST.RANGE
Synopsis
BINOM.DIST.RANGE(trials,p,start,end)
Arguments
trials: number of trials
p: probability of success in each trial
start: start of the interval
end: end of the interval, defaults to start
Note
If start, end or trials are non-integer they are truncated. If trials < 0 this function returns a #NUM! error. If p < 0 or p > 1 this function returns a #NUM! error. If start > end this function returns 0.
OpenDocument Format (ODF) Compatibility
This function is OpenFormula compatible.
BINOMDIST
Synopsis
BINOMDIST(n,trials,p,cumulative)
Arguments
n: number of successes
trials: number of trials
p: probability of success in each trial
cumulative: whether to evaluate the mass function or the cumulative distribution function
Note
If n or trials are non-integer they are truncated. If n < 0 or trials < 0 this function returns a #NUM! error. If n > trials this function returns a #NUM! error. If p < 0 or p > 1 this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
CAUCHY
Synopsis
CAUCHY(x,a,cumulative)
Arguments
x: number
a: scale parameter
cumulative: whether to evaluate the density function or the cumulative distribution function
Note
If a < 0 this function returns a #NUM! error. If cumulative is neither TRUE nor FALSE this function returns a #VALUE! error.
See also
CHIDIST
Synopsis
CHIDIST(x,dof)
Arguments
x: number
dof: number of degrees of freedom
Description
The survival function is 1 minus the cumulative distribution function.
Note
If dof is non-integer it is truncated. If dof < 1 this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
OpenDocument Format (ODF) Compatibility
CHIDIST(x,dof) is the OpenFormula function LEGACY.CHIDIST(x,dof).
CHIINV
Synopsis
CHIINV(p,dof)
Arguments
p: probability
dof: number of degrees of freedom
Description
The survival function is 1 minus the cumulative distribution function.
Note
If p < 0 or p > 1 or dof < 1 this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
OpenDocument Format (ODF) Compatibility
CHIINV(p,dof) is the OpenFormula function LEGACY.CHIDIST(p,dof).
CHITEST
Synopsis
CHITEST(actual_range,theoretical_range)
Arguments
actual_range: observed data
theoretical_range: expected values
Note
If the actual range is not an n by 1 or 1 by n range, but an n by m range, then CHITEST uses (n-1) times (m-1) as degrees of freedom. This is useful if the expected values were calculated from the observed value in a test of independence or test of homogeneity.
Microsoft Excel Compatibility
This function is Excel compatible.
OpenDocument Format (ODF) Compatibility
CHITEST is the OpenFormula function LEGACY.CHITEST.
CONFIDENCE
Synopsis
CONFIDENCE(alpha,stddev,size)
Arguments
alpha: significance level
stddev: population standard deviation
size: sample size
Note
This function requires the usually unknown population standard deviation. If size is non-integer it is truncated. If size < 0 this function returns a #NUM! error. If size is 0 this function returns a #DIV/0! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
CONFIDENCE.T
Synopsis
CONFIDENCE.T(alpha,stddev,size)
Arguments
alpha: significance level
stddev: sample standard deviation
size: sample size
Note
If stddev < 0 or = 0 this function returns a #NUM! error. If size is non-integer it is truncated. If size < 1 this function returns a #NUM! error. If size is 1 this function returns a #DIV/0! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
CORREL
Synopsis
CORREL(array1,array2)
Arguments
array1: first data set
array2: second data set
Description
Strings and empty cells are simply ignored.
Microsoft Excel Compatibility
This function is Excel compatible.
COUNT
Synopsis
COUNT(number1,number2,…)
Arguments
number1: first value
number2: second value
Microsoft Excel Compatibility
This function is Excel compatible.
See also
COUNTA
Synopsis
COUNTA(number1,number2,…)
Arguments
number1: first value
number2: second value
Microsoft Excel Compatibility
This function is Excel compatible.
COVAR
Synopsis
COVAR(array1,array2)
Arguments
array1: first data set
array2: set data set
Description
Strings and empty cells are simply ignored.
Microsoft Excel Compatibility
This function is Excel compatible.
COVARIANCE.S
Synopsis
COVARIANCE.S(array1,array2)
Arguments
array1: first data set
array2: set data set
Description
Strings and empty cells are simply ignored.
Microsoft Excel Compatibility
This function is Excel compatible.
CRITBINOM
Synopsis
CRITBINOM(trials,p,alpha)
Arguments
trials: number of trials
p: probability of success in each trial
alpha: significance level (area of the tail)
Note
If trials is a non-integer it is truncated. If trials < 0 this function returns a #NUM! error. If p < 0 or p > 1 this function returns a #NUM! error. If alpha < 0 or alpha > 1 this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
CRONBACH
Synopsis
CRONBACH(ref1,ref2,…)
Arguments
ref1: first data set
ref2: second data set
See also
VAR.
CVMTEST
Synopsis
CVMTEST(x)
Arguments
x: array of sample values
Description
This function returns an array with the first row giving the p-value of the Cramér-von Mises Test, the second row the test statistic of the test, and the third the number of observations in the sample.
Note
If there are less than 8 sample values, CVMTEST returns #VALUE!
DEVSQ
Synopsis
DEVSQ(number1,number2,…)
Arguments
number1: first value
number2: second value
Description
Strings and empty cells are simply ignored.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
EXPONDIST
Synopsis
EXPONDIST(x,y,cumulative)
Arguments
x: number
y: scale parameter
cumulative: whether to evaluate the density function or the cumulative distribution function
Description
If cumulative is false it will return: y * exp (-y*x), otherwise it will return 1 - exp (-y*x).
Note
If x < 0 or y <= 0 this will return an error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
EXPPOWDIST
Synopsis
EXPPOWDIST(x,a,b)
Arguments
x: number
a: scale parameter
b: scale parameter
Description
This distribution has been recommended for lifetime analysis when a U-shaped hazard function is desired. This corresponds to rapid failure once the product starts to wear out after a period of steady or even improving reliability.
See also
FDIST
Synopsis
FDIST(x,dof_of_num,dof_of_denom)
Arguments
x: number
dof_of_num: numerator degrees of freedom
dof_of_denom: denominator degrees of freedom
Description
The survival function is 1 minus the cumulative distribution function.
Note
If x < 0 this function returns a #NUM! error. If dof_of_num < 1 or dof_of_denom < 1, this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
OpenDocument Format (ODF) Compatibility
FDIST is the OpenFormula function LEGACY.FDIST.
See also
FINV.
FINV
Synopsis
FINV(p,dof_of_num,dof_of_denom)
Arguments
p: probability
dof_of_num: numerator degrees of freedom
dof_of_denom: denominator degrees of freedom
Description
The survival function is 1 minus the cumulative distribution function.
Note
If p < 0 or p > 1 this function returns a #NUM! error. If dof_of_num < 1 or dof_of_denom < 1 this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
OpenDocument Format (ODF) Compatibility
FINV is the OpenFormula function LEGACY.FINV.
See also
FISHER
Synopsis
FISHER(x)
Arguments
x: number
Note
If x is not a number, this function returns a #VALUE! error. If x <= -1 or x >= 1, this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
FISHERINV
Synopsis
FISHERINV(x)
Arguments
x: number
Note
If x is a non-number this function returns a #VALUE! error.
Microsoft Excel Compatibility
This function is Excel compatible.
FORECAST
Synopsis
FORECAST(x,known_ys,known_xs)
Arguments
x: x-value whose matching y-value should be forecast
known_ys: known y-values
known_xs: known x-values
Description
This function estimates a future value according to existing values using simple linear regression.
Note
If known_xs or known_ys contains no data entries or different number of data entries, this function returns a #N/A error. If the variance of the known_xs is zero, this function returns a #DIV/0 error.
Microsoft Excel Compatibility
This function is Excel compatible.
FREQUENCY
Synopsis
FREQUENCY(data_array,bins_array)
Arguments
data_array: data values
bins_array: array of cutoff values
Description
The results are given as an array.
If the bins_array is empty, this function returns the number of data points in data_array.
Microsoft Excel Compatibility
This function is Excel compatible.
FTEST
Synopsis
FTEST(array1,array2)
Arguments
array1: sample from the first population
array2: sample from the second population
Microsoft Excel Compatibility
This function is Excel compatible.
GAMMADIST
Synopsis
GAMMADIST(x,alpha,beta,cumulative)
Arguments
x: number
alpha: scale parameter
beta: scale parameter
cumulative: whether to evaluate the density function or the cumulative distribution function
Note
If x < 0 this function returns a #NUM! error. If alpha <= 0 or beta <= 0, this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
GAMMAINV
Synopsis
GAMMAINV(p,alpha,beta)
Arguments
p: probability
alpha: scale parameter
beta: scale parameter
Note
If p < 0 or p > 1 this function returns a #NUM! error. If alpha <= 0 or beta <= 0 this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
GEOMDIST
Synopsis
GEOMDIST(k,p,cumulative)
Arguments
k: number of trials
p: probability of success in any trial
cumulative: whether to evaluate the mass function or the cumulative distribution function
Note
If k < 0 this function returns a #NUM! error. If p < 0 or p > 1 this function returns a #NUM! error. If cumulative is neither TRUE nor FALSE this function returns a #VALUE! error.
See also
GEOMEAN
Synopsis
GEOMEAN(number1,number2,…)
Arguments
number1: first value
number2: second value
Description
The geometric mean is equal to the Nth root of the product of the N values.
Microsoft Excel Compatibility
This function is Excel compatible.
GROWTH
Synopsis
GROWTH(known_ys,known_xs,new_xs,affine)
Arguments
known_ys: known y-values
known_xs: known x-values; defaults to the array {1, 2, 3, …}
new_xs: x-values for which to estimate the y-values; defaults to known_xs
affine: if true, the model contains a constant term, defaults to true
Description
GROWTH function applies the “least squares” method to fit an exponential curve to your data and predicts the exponential growth by using this curve.
GROWTH returns an array having one column and a row for each data point in new_xs.
Note
If known_ys and known_xs have unequal number of data points, this function returns a #NUM! error.
HARMEAN
Synopsis
HARMEAN(number1,number2,…)
Arguments
number1: first value
number2: second value
Description
The harmonic mean of N data points is N divided by the sum of the reciprocals of the data points).
Microsoft Excel Compatibility
This function is Excel compatible.
HYPGEOMDIST
Synopsis
HYPGEOMDIST(x,n,M,N,cumulative)
Arguments
x: number of successes
n: sample size
M: number of possible successes in the population
N: population size
cumulative: whether to evaluate the mass function or the cumulative distribution function
Note
If x,n,M or N is a non-integer it is truncated. If x,n,M or N < 0 this function returns a #NUM! error. If x > M or n > N this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
INTERCEPT
Synopsis
INTERCEPT(known_ys,known_xs)
Arguments
known_ys: known y-values
known_xs: known x-values
Note
If known_xs or known_ys contains no data entries or different number of data entries, this function returns a #N/A error. If the variance of the known_xs is zero, this function returns #DIV/0 error.
Microsoft Excel Compatibility
This function is Excel compatible.
KURT
Synopsis
KURT(number1,number2,…)
Arguments
number1: first value
number2: second value
Description
Strings and empty cells are simply ignored.
Note
This is only meaningful if the underlying distribution really has a fourth moment. The kurtosis is offset by three such that a normal distribution will have zero kurtosis. If fewer than four numbers are given or all of them are equal this function returns a #DIV/0! error.
Microsoft Excel Compatibility
This function is Excel compatible.
KURTP
Synopsis
KURTP(number1,number2,…)
Arguments
number1: first value
number2: second value
Description
Strings and empty cells are simply ignored.
Note
If fewer than two numbers are given or all of them are equal this function returns a #DIV/0! error.
LANDAU
Synopsis
LANDAU(x)
Arguments
x: number
See also
LAPLACE
Synopsis
LAPLACE(x,a)
Arguments
x: number
a: mean
See also
LARGE
Synopsis
LARGE(data,k)
Arguments
data: data set
k: which value to find
Note
If data set is empty this function returns a #NUM! error. If k <= 0 or k is greater than the number of data items given this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
LEVERAGE
Synopsis
LEVERAGE(A)
Arguments
A: a matrix
Description
Returns the diagonal of A (A^T A)^-1 A^T as a column vector.
Note
If the matrix is singular, #VALUE! is returned.
LINEST
Synopsis
LINEST(known_ys,known_xs,affine,stats)
Arguments
known_ys: vector of values of dependent variable
known_xs: array of values of independent variables, defaults to a single vector {1,…,n}
affine: if true, the model contains a constant term, defaults to true
stats: if true, some additional statistics are provided, defaults to false
Description
This function returns an array with the first row giving the regression coefficients for the independent variables x_m, x_(m-1),…,x_2, x_1 followed by the y-intercept if affine is true.
If stats is true, the second row contains the corresponding standard errors of the regression coefficients. In this case, the third row contains the R^2 value and the standard error for the predicted value. The fourth row contains the observed F value and its degrees of freedom. Finally, the fifth row contains the regression sum of squares and the residual sum of squares.
If affine is false, R^2 is the uncentered version of the coefficient of determination; that is the proportion of the sum of squares explained by the model.
Note
If the length of known_ys does not match the corresponding length of known_xs, this function returns a #NUM! error.
LKSTEST
Synopsis
LKSTEST(x)
Arguments
x: array of sample values
Description
This function returns an array with the first row giving the p-value of the Lilliefors (Kolmogorov-Smirnov) Test, the second row the test statistic of the test, and the third the number of observations in the sample.
Note
If there are less than 5 sample values, LKSTEST returns #VALUE!
LOGEST
Synopsis
LOGEST(known_ys,known_xs,affine,stat)
Arguments
known_ys: known y-values
known_xs: known x-values; default to an array {1, 2, 3, …}
affine: if true, the model contains a constant term, defaults to true
stat: if true, extra statistical information will be returned; defaults to FALSE
Description
LOGEST function applies the “least squares” method to fit an exponential curve of the form y = b * m{1}^x{1} * m{2}^x{2}... to your data.
LOGEST returns an array { m{n},m{n-1}, ...,m{1},b }.
Note
Extra statistical information is written below the regression line coefficients in the result array. Extra statistical information consists of four rows of data. In the first row the standard error values for the coefficients m1, (m2, ...), b are represented. The second row contains the square of R and the standard error for the y estimate. The third row contains the F-observed value and the degrees of freedom. The last row contains the regression sum of squares and the residual sum of squares. If known_ys and known_xs have unequal number of data points, this function returns a #NUM! error.
LOGFIT
Synopsis
LOGFIT(known_ys,known_xs)
Arguments
known_ys: known y-values
known_xs: known x-values
Description
LOGFIT function applies the “least squares” method to fit the logarithmic equation y = a + b * ln(sign * (x - c)) , sign = +1 or -1 to your data. The graph of the equation is a logarithmic curve moved horizontally by c and possibly mirrored across the y-axis (if sign = -1).
LOGFIT returns an array having five columns and one row. `Sign' is given in the first column, `a', `b', and `c' are given in columns 2 to 4. Column 5 holds the sum of squared residuals.
Note
An error is returned when there are less than 3 different x's or y's, or when the shape of the point cloud is too different from a ``logarithmic'' one. You can use the above formula = a + b * ln(sign * (x - c)) or rearrange it to = (exp((y - a) / b)) / sign + c to compute unknown y's or x's, respectively. This is non-linear fitting by trial-and-error. The accuracy of `c' is: width of x-range -> rounded to the next smaller (10^integer), times 0.000001. There might be cases in which the returned fit is not the best possible.
LOGINV
Synopsis
LOGINV(p,mean,stddev)
Arguments
p: probability
mean: mean
stddev: standard deviation
Note
If p < 0 or p > 1 or stddev <= 0 this function returns #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
EXP, LN, LOG, LOG10, LOGNORMDIST.
LOGISTIC
Synopsis
LOGISTIC(x,a)
Arguments
x: number
a: scale parameter
See also
LOGNORMDIST
Synopsis
LOGNORMDIST(x,mean,stddev)
Arguments
x: number
mean: mean
stddev: standard deviation
Note
If stddev = 0 LOGNORMDIST returns a #DIV/0! error. If x <= 0, mean < 0 or stddev <= 0 this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
LOGREG
Synopsis
LOGREG(known_ys,known_xs,affine,stat)
Arguments
known_ys: known y-values
known_xs: known x-values; defaults to the array {1, 2, 3, …}
affine: if true, the model contains a constant term, defaults to true
stat: if true, extra statistical information will be returned; defaults to FALSE
Description
LOGREG function transforms your x's to z=ln(x) and applies the “least squares” method to fit the linear equation y = m * z + b to your y's and z's --- equivalent to fitting the equation y = m * ln(x) + b to y's and x's. LOGREG returns an array having two columns and one row. m is given in the first column and b in the second.
Any extra statistical information is written below m and b in the result array. This extra statistical information consists of four rows of data: In the first row the standard error values for the coefficients m, b are given. The second row contains the square of R and the standard error for the y estimate. The third row contains the F-observed value and the degrees of freedom. The last row contains the regression sum of squares and the residual sum of squares. The default of stat is FALSE.
Note
If known_ys and known_xs have unequal number of data points, this function returns a #NUM! error.
MAX
Synopsis
MAX(number1,number2,…)
Arguments
number1: first value
number2: second value
Microsoft Excel Compatibility
This function is Excel compatible.
MAXA
Synopsis
MAXA(number1,number2,…)
Arguments
number1: first value
number2: second value
Description
Numbers, text and logical values are included in the calculation too. If the cell contains text or the argument evaluates to FALSE, it is counted as value zero (0). If the argument evaluates to TRUE, it is counted as one (1). Note that empty cells are not counted.
Microsoft Excel Compatibility
This function is Excel compatible.
MEDIAN
Synopsis
MEDIAN(number1,number2,…)
Arguments
number1: first value
number2: second value
Description
Strings and empty cells are simply ignored.
Note
If even numbers are given MEDIAN returns the average of the two numbers in the center.
Microsoft Excel Compatibility
This function is Excel compatible.
MIN
Synopsis
MIN(number1,number2,…)
Arguments
number1: first value
number2: second value
Microsoft Excel Compatibility
This function is Excel compatible.
MINA
Synopsis
MINA(number1,number2,…)
Arguments
number1: first value
number2: second value
Description
Numbers, text and logical values are included in the calculation too. If the cell contains text or the argument evaluates to FALSE, it is counted as value zero (0). If the argument evaluates to TRUE, it is counted as one (1). Note that empty cells are not counted.
Microsoft Excel Compatibility
This function is Excel compatible.
MODE
Synopsis
MODE(number1,number2,…)
Arguments
number1: first value
number2: second value
Description
Strings and empty cells are simply ignored.
If the data set does not contain any duplicates this function returns a #N/A error.
Microsoft Excel Compatibility
This function is Excel compatible.
MODE.MULT
Synopsis
MODE.MULT(number1,number2,…)
Arguments
number1: first value
number2: second value
Description
Strings and empty cells are simply ignored.
If the data set does not contain any duplicates this function returns a #N/A error.
Microsoft Excel Compatibility
This function is Excel compatible.
NEGBINOMDIST
Synopsis
NEGBINOMDIST(f,t,p)
Arguments
f: number of failures
t: threshold number of successes
p: probability of a success
Note
If f or t is a non-integer it is truncated. If (f + t -1) <= 0 this function returns a #NUM! error. If p < 0 or p > 1 this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
BINOMDIST, COMBIN, FACT, HYPGEOMDIST, PERMUT.
NORMDIST
Synopsis
NORMDIST(x,mean,stddev,cumulative)
Arguments
x: number
mean: mean of the distribution
stddev: standard deviation of the distribution
cumulative: whether to evaluate the density function or the cumulative distribution function
Note
If stddev is 0 this function returns a #DIV/0! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
NORMINV
Synopsis
NORMINV(p,mean,stddev)
Arguments
p: probability
mean: mean of the distribution
stddev: standard deviation of the distribution
Note
If p < 0 or p > 1 or stddev <= 0 this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
NORMSDIST
Synopsis
NORMSDIST(x)
Arguments
x: number
Microsoft Excel Compatibility
This function is Excel compatible.
OpenDocument Format (ODF) Compatibility
NORMSDIST is the OpenFormula function LEGACY.NORMSDIST.
See also
NORMSINV
Synopsis
NORMSINV(p)
Arguments
p: given probability
Note
If p < 0 or p > 1 this function returns #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
OpenDocument Format (ODF) Compatibility
NORMSINV is the OpenFormula function LEGACY.NORMSINV.
See also
PARETO
Synopsis
PARETO(x,a,b)
Arguments
x: number
a: exponent
b: scale parameter
See also
PEARSON
Synopsis
PEARSON(array1,array2)
Arguments
array1: first component values
array2: second component values
Description
Strings and empty cells are simply ignored.
Microsoft Excel Compatibility
This function is Excel compatible.
PERCENTILE
Synopsis
PERCENTILE(array,k)
Arguments
array: data points
k: which percentile to calculate
Note
If array is empty, this function returns a #NUM! error. If k < 0 or k > 1, this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
PERCENTILE.EXC
Synopsis
PERCENTILE.EXC(array,k)
Arguments
array: data points
k: which percentile to calculate
Note
If array is empty, this function returns a #NUM! error. If k < 0 or k > 1, this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
PERCENTRANK
Synopsis
PERCENTRANK(array,x,significance)
Arguments
array: range of numeric values
x: data point to be ranked
significance: number of significant digits, defaults to 3
Note
If array contains no data points, this function returns a #NUM! error. If significance is less than one, this function returns a #NUM! error. If x exceeds the largest value or is less than the smallest value in array, this function returns an #N/A error. If x does not match any of the values in array or x matches more than once, this function interpolates the returned value.
PERCENTRANK.EXC
Synopsis
PERCENTRANK.EXC(array,x,significance)
Arguments
array: range of numeric values
x: data point to be ranked
significance: number of significant digits, defaults to 3
Note
If array contains no data points, this function returns a #NUM! error. If significance is less than one, this function returns a #NUM! error. If x exceeds the largest value or is less than the smallest value in array, this function returns an #N/A error. If x does not match any of the values in array or x matches more than once, this function interpolates the returned value.
See also
LARGE, MAX, MEDIAN, MIN, PERCENTILE, PERCENTILE.EXC, QUARTILE, QUARTILE.EXC, SMALL.
PERMUT
Synopsis
PERMUT(n,k)
Arguments
n: size of the base set
k: number of elements in each permutation
Note
If n = 0 this function returns a #NUM! error. If n < k this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
PERMUTATIONA
Synopsis
PERMUTATIONA(x,y)
Arguments
x: total number of objects
y: number of selected objects
Note
If both x and y equal 0, PERMUTATIONA returns 1. If x < 0 or y < 0, PERMUTATIONA returns #NUM! If x or y are not integers, they are truncated.
OpenDocument Format (ODF) Compatibility
This function is OpenFormula compatible.
See also
POISSON
Synopsis
POISSON(x,mean,cumulative)
Arguments
x: number of events
mean: mean of the distribution
cumulative: whether to evaluate the mass function or the cumulative distribution function
Note
If x is a non-integer it is truncated. If x < 0 this function returns a #NUM! error. If mean <= 0 POISSON returns the #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
PROB
Synopsis
PROB(x_range,prob_range,lower_limit,upper_limit)
Arguments
x_range: possible values
prob_range: probabilities of the corresponding values
lower_limit: lower interval limit
upper_limit: upper interval limit, defaults to lower_limit
Note
If the sum of the probabilities in prob_range is not equal to 1 this function returns a #NUM! error. If any value in prob_range is <=0 or > 1, this function returns a #NUM! error. If x_range and prob_range contain a different number of data entries, this function returns a #N/A error.
Microsoft Excel Compatibility
This function is Excel compatible.
QUARTILE
Synopsis
QUARTILE(array,quart)
Arguments
array: data points
quart: a number from 0 to 4, indicating which quartile to calculate
Note
If array is empty, this function returns a #NUM! error. If quart < 0 or quart > 4, this function returns a #NUM! error. If quart = 0, the smallest value of array to be returned. If quart is not an integer, it is truncated.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
LARGE, MAX, MEDIAN, MIN, PERCENTILE, QUARTILE.EXC, SMALL.
QUARTILE.EXC
Synopsis
QUARTILE.EXC(array,quart)
Arguments
array: data points
quart: a number from 1 to 3, indicating which quartile to calculate
Note
If array is empty, this function returns a #NUM! error. If quart < 0 or quart > 4, this function returns a #NUM! error. If quart = 0, the smallest value of array to be returned. If quart is not an integer, it is truncated.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
LARGE, MAX, MEDIAN, MIN, PERCENTILE, PERCENTILE.EXC, QUARTILE, SMALL.
R.DBETA
Synopsis
R.DBETA(x,a,b,give_log)
Arguments
x: observation
a: the first shape parameter of the distribution
b: the second scale parameter of the distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the beta distribution.
R.DBINOM
Synopsis
R.DBINOM(x,n,psuc,give_log)
Arguments
x: observation
n: the number of trials
psuc: the probability of success in each trial
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the binomial distribution.
R.DCAUCHY
Synopsis
R.DCAUCHY(x,location,scale,give_log)
Arguments
x: observation
location: the center of the distribution
scale: the scale parameter of the distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the Cauchy distribution.
R.DCHISQ
Synopsis
R.DCHISQ(x,df,give_log)
Arguments
x: observation
df: the number of degrees of freedom of the distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the chi-square distribution.
OpenDocument Format (ODF) Compatibility
A two argument invocation R.DCHISQ(x,df) is exported to OpenFormula as CHISQDIST(x,df,FALSE()).
R.DEXP
Synopsis
R.DEXP(x,scale,give_log)
Arguments
x: observation
scale: the scale parameter of the distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the exponential distribution.
R.DF
Synopsis
R.DF(x,n1,n2,give_log)
Arguments
x: observation
n1: the first number of degrees of freedom of the distribution
n2: the second number of degrees of freedom of the distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the F distribution.
R.DGAMMA
Synopsis
R.DGAMMA(x,shape,scale,give_log)
Arguments
x: observation
shape: the shape parameter of the distribution
scale: the scale parameter of the distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the gamma distribution.
R.DGEOM
Synopsis
R.DGEOM(x,psuc,give_log)
Arguments
x: observation
psuc: the probability of success in each trial
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the geometric distribution.
R.DGUMBEL
Synopsis
R.DGUMBEL(x,mu,beta,give_log)
Arguments
x: observation
mu: the location parameter of freedom of the distribution
beta: the scale parameter of freedom of the distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the Gumbel distribution.
R.DHYPER
Synopsis
R.DHYPER(x,r,b,n,give_log)
Arguments
x: observation
r: the number of red balls
b: the number of black balls
n: the number of balls drawn
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the hypergeometric distribution.
R.DLNORM
Synopsis
R.DLNORM(x,logmean,logsd,give_log)
Arguments
x: observation
logmean: mean of the underlying normal distribution
logsd: standard deviation of the underlying normal distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the log-normal distribution.
R.DNBINOM
Synopsis
R.DNBINOM(x,n,psuc,give_log)
Arguments
x: observation (number of failures)
n: required number of successes
psuc: the probability of success in each trial
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the negative binomial distribution.
R.DNORM
Synopsis
R.DNORM(x,mu,sigma,give_log)
Arguments
x: observation
mu: mean of the distribution
sigma: standard deviation of the distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the normal distribution.
R.DPOIS
Synopsis
R.DPOIS(x,lambda,give_log)
Arguments
x: observation
lambda: the mean of the distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the Poisson distribution.
R.DRAYLEIGH
Synopsis
R.DRAYLEIGH(x,scale,give_log)
Arguments
x: observation
scale: the scale parameter of the distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the Rayleigh distribution.
See also
R.DSNORM
Synopsis
R.DSNORM(x,shape,location,scale,give_log)
Arguments
x: observation
shape: the shape parameter of the distribution
location: the location parameter of the distribution
scale: the scale parameter of the distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the skew-normal distribution.
R.DST
Synopsis
R.DST(x,n,shape,give_log)
Arguments
x: observation
n: the number of degrees of freedom of the distribution
shape: the shape parameter of the distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the skew-t distribution.
R.DT
Synopsis
R.DT(x,n,give_log)
Arguments
x: observation
n: the number of degrees of freedom of the distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the Student t distribution.
R.DWEIBULL
Synopsis
R.DWEIBULL(x,shape,scale,give_log)
Arguments
x: observation
shape: the shape parameter of the distribution
scale: the scale parameter of the distribution
give_log: if true, log of the result will be returned instead
Description
This function returns the probability density function of the Weibull distribution.
See also
R.PBETA
Synopsis
R.PBETA(x,a,b,lower_tail,log_p)
Arguments
x: observation
a: the first shape parameter of the distribution
b: the second scale parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the beta distribution.
R.PBINOM
Synopsis
R.PBINOM(x,n,psuc,lower_tail,log_p)
Arguments
x: observation
n: the number of trials
psuc: the probability of success in each trial
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the binomial distribution.
R.PCAUCHY
Synopsis
R.PCAUCHY(x,location,scale,lower_tail,log_p)
Arguments
x: observation
location: the center of the distribution
scale: the scale parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the Cauchy distribution.
R.PCHISQ
Synopsis
R.PCHISQ(x,df,lower_tail,log_p)
Arguments
x: observation
df: the number of degrees of freedom of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the chi-square distribution.
OpenDocument Format (ODF) Compatibility
A two argument invocation R.PCHISQ(x,df) is exported to OpenFormula as CHISQDIST(x,df).
R.PEXP
Synopsis
R.PEXP(x,scale,lower_tail,log_p)
Arguments
x: observation
scale: the scale parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the exponential distribution.
R.PF
Synopsis
R.PF(x,n1,n2,lower_tail,log_p)
Arguments
x: observation
n1: the first number of degrees of freedom of the distribution
n2: the second number of degrees of freedom of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the F distribution.
R.PGAMMA
Synopsis
R.PGAMMA(x,shape,scale,lower_tail,log_p)
Arguments
x: observation
shape: the shape parameter of the distribution
scale: the scale parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the gamma distribution.
R.PGEOM
Synopsis
R.PGEOM(x,psuc,lower_tail,log_p)
Arguments
x: observation
psuc: the probability of success in each trial
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the geometric distribution.
R.PGUMBEL
Synopsis
R.PGUMBEL(x,mu,beta,lower_tail,log_p)
Arguments
x: observation
mu: the location parameter of freedom of the distribution
beta: the scale parameter of freedom of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the Gumbel distribution.
R.PHYPER
Synopsis
R.PHYPER(x,r,b,n,lower_tail,log_p)
Arguments
x: observation
r: the number of red balls
b: the number of black balls
n: the number of balls drawn
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the hypergeometric distribution.
R.PLNORM
Synopsis
R.PLNORM(x,logmean,logsd,lower_tail,log_p)
Arguments
x: observation
logmean: mean of the underlying normal distribution
logsd: standard deviation of the underlying normal distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the log-normal distribution.
R.PNBINOM
Synopsis
R.PNBINOM(x,n,psuc,lower_tail,log_p)
Arguments
x: observation (number of failures)
n: required number of successes
psuc: the probability of success in each trial
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the negative binomial distribution.
R.PNORM
Synopsis
R.PNORM(x,mu,sigma,lower_tail,log_p)
Arguments
x: observation
mu: mean of the distribution
sigma: standard deviation of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the normal distribution.
R.PPOIS
Synopsis
R.PPOIS(x,lambda,lower_tail,log_p)
Arguments
x: observation
lambda: the mean of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the Poisson distribution.
R.PRAYLEIGH
Synopsis
R.PRAYLEIGH(x,scale,lower_tail,log_p)
Arguments
x: observation
scale: the scale parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the Rayleigh distribution.
See also
R.PSNORM
Synopsis
R.PSNORM(x,shape,location,scale,lower_tail,log_p)
Arguments
x: observation
shape: the shape parameter of the distribution
location: the location parameter of the distribution
scale: the scale parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the skew-normal distribution.
R.PST
Synopsis
R.PST(x,n,shape,lower_tail,log_p)
Arguments
x: observation
n: the number of degrees of freedom of the distribution
shape: the shape parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the skew-t distribution.
R.PT
Synopsis
R.PT(x,n,lower_tail,log_p)
Arguments
x: observation
n: the number of degrees of freedom of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the Student t distribution.
R.PTUKEY
Synopsis
R.PTUKEY(x,nmeans,df,nranges,lower_tail,log_p)
Arguments
x: observation
nmeans: the number of means
df: the number of degrees of freedom of the distribution
nranges: the number of ranges; default is 1
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the Studentized range distribution.
See also
R.PWEIBULL
Synopsis
R.PWEIBULL(x,shape,scale,lower_tail,log_p)
Arguments
x: observation
shape: the shape parameter of the distribution
scale: the scale parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the cumulative distribution function of the Weibull distribution.
See also
R.QBETA
Synopsis
R.QBETA(p,a,b,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
a: the first shape parameter of the distribution
b: the second scale parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the beta distribution.
R.QBINOM
Synopsis
R.QBINOM(p,n,psuc,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
n: the number of trials
psuc: the probability of success in each trial
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the binomial distribution.
R.QCAUCHY
Synopsis
R.QCAUCHY(p,location,scale,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
location: the center of the distribution
scale: the scale parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the Cauchy distribution.
R.QCHISQ
Synopsis
R.QCHISQ(p,df,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
df: the number of degrees of freedom of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the chi-square distribution.
OpenDocument Format (ODF) Compatibility
A two argument invocation R.QCHISQ(p,df) is exported to OpenFormula as CHISQINV(p,df).
R.QEXP
Synopsis
R.QEXP(p,scale,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
scale: the scale parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the exponential distribution.
R.QF
Synopsis
R.QF(p,n1,n2,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
n1: the first number of degrees of freedom of the distribution
n2: the second number of degrees of freedom of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the F distribution.
R.QGAMMA
Synopsis
R.QGAMMA(p,shape,scale,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
shape: the shape parameter of the distribution
scale: the scale parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the gamma distribution.
R.QGEOM
Synopsis
R.QGEOM(p,psuc,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
psuc: the probability of success in each trial
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the geometric distribution.
R.QGUMBEL
Synopsis
R.QGUMBEL(p,mu,beta,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
mu: the location parameter of freedom of the distribution
beta: the scale parameter of freedom of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the Gumbel distribution.
R.QHYPER
Synopsis
R.QHYPER(p,r,b,n,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
r: the number of red balls
b: the number of black balls
n: the number of balls drawn
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the hypergeometric distribution.
R.QLNORM
Synopsis
R.QLNORM(p,logmean,logsd,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
logmean: mean of the underlying normal distribution
logsd: standard deviation of the underlying normal distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the log-normal distribution.
R.QNBINOM
Synopsis
R.QNBINOM(p,n,psuc,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
n: required number of successes
psuc: the probability of success in each trial
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the negative binomial distribution.
R.QNORM
Synopsis
R.QNORM(p,mu,sigma,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
mu: mean of the distribution
sigma: standard deviation of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the normal distribution.
R.QPOIS
Synopsis
R.QPOIS(p,lambda,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
lambda: the mean of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the Poisson distribution.
R.QRAYLEIGH
Synopsis
R.QRAYLEIGH(p,scale,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
scale: the scale parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the Rayleigh distribution.
See also
R.QSNORM
Synopsis
R.QSNORM(p,shape,location,scale,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
shape: the shape parameter of the distribution
location: the location parameter of the distribution
scale: the scale parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the skew-normal distribution.
R.QST
Synopsis
R.QST(p,n,shape,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
n: the number of degrees of freedom of the distribution
shape: the shape parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the skew-t distribution.
R.QT
Synopsis
R.QT(p,n,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
n: the number of degrees of freedom of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the Student t distribution.
R.QTUKEY
Synopsis
R.QTUKEY(p,nmeans,df,nranges,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
nmeans: the number of means
df: the number of degrees of freedom of the distribution
nranges: the number of ranges; default is 1
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the Studentized range distribution.
See also
R.QWEIBULL
Synopsis
R.QWEIBULL(p,shape,scale,lower_tail,log_p)
Arguments
p: probability or natural logarithm of the probability
shape: the shape parameter of the distribution
scale: the scale parameter of the distribution
lower_tail: if true (the default), the lower tail of the distribution is considered
log_p: if true, the natural logarithm of the probability is given or returned; defaults to false
Description
This function returns the probability quantile function, i.e., the inverse of the cumulative distribution function, of the Weibull distribution.
See also
RANK
Synopsis
RANK(x,ref,order)
Arguments
x: number whose rank you want to find
ref: list of numbers
order: 0 (descending order) or non-zero (ascending order); defaults to 0
Note
In case of a tie, RANK returns the largest possible rank.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
RANK.AVG
Synopsis
RANK.AVG(x,ref,order)
Arguments
x: number whose rank you want to find
ref: list of numbers
order: 0 (descending order) or non-zero (ascending order); defaults to 0
Note
In case of a tie, RANK.AVG returns the average rank.
Microsoft Excel Compatibility
This function is Excel 2010 compatible.
See also
RAYLEIGH
Synopsis
RAYLEIGH(x,sigma)
Arguments
x: number
sigma: scale parameter
See also
RAYLEIGHTAIL
Synopsis
RAYLEIGHTAIL(x,a,sigma)
Arguments
x: number
a: lower limit
sigma: scale parameter
See also
RSQ
Synopsis
RSQ(array1,array2)
Arguments
array1: first component values
array2: second component values
Description
Strings and empty cells are simply ignored.
Microsoft Excel Compatibility
This function is Excel compatible.
SFTEST
Synopsis
SFTEST(x)
Arguments
x: array of sample values
Description
This function returns an array with the first row giving the p-value of the Shapiro-Francia Test, the second row the test statistic of the test, and the third the number of observations in the sample.
Note
If there are less than 5 or more than 5000 sample values, SFTEST returns #VALUE!
SKEW
Synopsis
SKEW(number1,number2,…)
Arguments
number1: first value
number2: second value
Description
Strings and empty cells are simply ignored.
Note
This is only meaningful if the underlying distribution really has a third moment. The skewness of a symmetric (e.g., normal) distribution is zero. If less than three numbers are given, this function returns a #DIV/0! error.
Microsoft Excel Compatibility
This function is Excel compatible.
SKEWP
Synopsis
SKEWP(number1,number2,…)
Arguments
number1: first value
number2: second value
Description
Strings and empty cells are simply ignored.
Note
If less than two numbers are given, SKEWP returns a #DIV/0! error.
SLOPE
Synopsis
SLOPE(known_ys,known_xs)
Arguments
known_ys: known y-values
known_xs: known x-values
Note
If known_xs or known_ys contains no data entries or different number of data entries, this function returns a #N/A error. If the variance of the known_xs is zero, this function returns #DIV/0 error.
Microsoft Excel Compatibility
This function is Excel compatible.
SMALL
Synopsis
SMALL(data,k)
Arguments
data: data set
k: which value to find
Note
If data set is empty this function returns a #NUM! error. If k <= 0 or k is greater than the number of data items given this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
SNORM.DIST.RANGE
Synopsis
SNORM.DIST.RANGE(x1,x2)
Arguments
x1: start of the interval
x2: end of the interval
Description
This function returns the cumulative probability over a range of the standard normal distribution; that is the integral over the probability density function from x1 to x2.
Note
If x1>x2, this function returns a negative value.
SSMEDIAN
Synopsis
SSMEDIAN(array,interval)
Arguments
array: data set
interval: length of each grouping interval, defaults to 1
Description
The data are assumed to be grouped into intervals of width interval. Each data point in array is the midpoint of the interval containing the true value. The median is calculated by interpolation within the median interval (the interval containing the median value), assuming that the true values within that interval are distributed uniformly:
median = L + interval*(N/2 - CF)/F
where:
L = the lower limit of the median interval
N = the total number of data points
CF = the number of data points below the median interval
F = the number of data points in the median interval
Note
If array is empty, this function returns a #NUM! error. If interval <= 0, this function returns a #NUM! error. SSMEDIAN does not check whether the data points are at least interval apart.
See also
STANDARDIZE
Synopsis
STANDARDIZE(x,mean,stddev)
Arguments
x: value
mean: mean of the original distribution
stddev: standard deviation of the original distribution
Note
If stddev is 0 this function returns a #DIV/0! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
STDEV
Synopsis
STDEV(area1,area2,…)
Arguments
area1: first cell area
area2: second cell area
Description
STDEV is also known as the N-1-standard deviation.
To obtain the population standard deviation of a whole population use STDEVP.
Microsoft Excel Compatibility
This function is Excel compatible.
STDEVA
Synopsis
STDEVA(area1,area2,…)
Arguments
area1: first cell area
area2: second cell area
Description
STDEVA is also known as the N-1-standard deviation.
To obtain the population standard deviation of a whole population use STDEVPA.
Numbers, text and logical values are included in the calculation too. If the cell contains text or the argument evaluates to FALSE, it is counted as value zero (0). If the argument evaluates to TRUE, it is counted as one (1). Note that empty cells are not counted.
Microsoft Excel Compatibility
This function is Excel compatible.
STDEVP
Synopsis
STDEVP(area1,area2,…)
Arguments
area1: first cell area
area2: second cell area
Description
This is also known as the N-standard deviation
Microsoft Excel Compatibility
This function is Excel compatible.
STDEVPA
Synopsis
STDEVPA(area1,area2,…)
Arguments
area1: first cell area
area2: second cell area
Description
This is also known as the N-standard deviation
Numbers, text and logical values are included in the calculation too. If the cell contains text or the argument evaluates to FALSE, it is counted as value zero (0). If the argument evaluates to TRUE, it is counted as one (1). Note that empty cells are not counted.
Microsoft Excel Compatibility
This function is Excel compatible.
STEYX
Synopsis
STEYX(known_ys,known_xs)
Arguments
known_ys: known y-values
known_xs: known x-values
Note
If known_ys and known_xs are empty or have a different number of arguments then this function returns a #N/A error.
Microsoft Excel Compatibility
This function is Excel compatible.
SUBTOTAL
Synopsis
SUBTOTAL(function_nbr,ref1,ref2,…)
Arguments
function_nbr: determines which function to use according to the following table:
1 AVERAGE
2 COUNT
3 COUNTA
4 MAX
5 MIN
6 PRODUCT
7 STDEV
8 STDEVP
9 SUM
10 VAR
11 VARP
ref1: first value
ref2: second value
Microsoft Excel Compatibility
This function is Excel compatible.
TDIST
Synopsis
TDIST(x,dof,tails)
Arguments
x: number
dof: number of degrees of freedom
tails: 1 or 2
Description
The survival function is 1 minus the cumulative distribution function.
This function is Excel compatible for non-negative x.
Note
If dof < 1 this function returns a #NUM! error. If tails is neither 1 or 2 this function returns a #NUM! error. The parameterization of this function is different from what is used for, e.g., NORMSDIST. This is a common source of mistakes, but necessary for compatibility.
TINV
Synopsis
TINV(p,dof)
Arguments
p: probability in both tails
dof: number of degrees of freedom
Description
This function returns the non-negative value x such that the area under the Student t density with dof degrees of freedom to the right of x is p/2.
Note
If p < 0 or p > 1 or dof < 1 this function returns a #NUM! error. The parameterization of this function is different from what is used for, e.g., NORMSINV. This is a common source of mistakes, but necessary for compatibility.
Microsoft Excel Compatibility
This function is Excel compatible.
TREND
Synopsis
TREND(known_ys,known_xs,new_xs,affine)
Arguments
known_ys: vector of values of dependent variable
known_xs: array of values of independent variables, defaults to a single vector {1,…,n}
new_xs: array of x-values for which to estimate the y-values; defaults to known_xs
affine: if true, the model contains a constant term, defaults to true
Note
If the length of known_ys does not match the corresponding length of known_xs, this function returns a #NUM! error.
See also
TRIMMEAN
Synopsis
TRIMMEAN(ref,fraction)
Arguments
ref: list of numbers whose mean you want to calculate
fraction: fraction of the data set excluded from the mean
Description
If fraction=0.2 and the data set contains 40 numbers, 8 numbers are trimmed from the data set (40 x 0.2): the 4 largest and the 4 smallest. To avoid a bias, the number of points to be excluded is always rounded down to the nearest even number.
Microsoft Excel Compatibility
This function is Excel compatible.
TTEST
Synopsis
TTEST(array1,array2,tails,type)
Arguments
array1: sample from the first population
array2: sample from the second population
tails: number of tails to consider
type: Type of test to perform. 1 indicates a test for paired variables, 2 a test of unpaired variables with equal variances, and 3 a test of unpaired variables with unequal variances
Note
If the data sets contain a different number of data points and the test is paired (type one), TTEST returns the #N/A error. tails and type are truncated to integers. If tails is not one or two, this function returns a #NUM! error. If type is any other than one, two, or three, this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
VAR
Synopsis
VAR(area1,area2,…)
Arguments
area1: first cell area
area2: second cell area
Description
VAR is also known as the N-1-variance.
Note
Since the N-1-variance includes Bessel's correction, whereas the N-variance calculated by VARPA or VARP does not, under reasonable conditions the N-1-variance is an unbiased estimator of the variance of the population from which the sample is drawn.
Microsoft Excel Compatibility
This function is Excel compatible.
VARA
Synopsis
VARA(area1,area2,…)
Arguments
area1: first cell area
area2: second cell area
Description
VARA is also known as the N-1-variance.
To get the true variance of a complete population use VARPA.
Numbers, text and logical values are included in the calculation too. If the cell contains text or the argument evaluates to FALSE, it is counted as value zero (0). If the argument evaluates to TRUE, it is counted as one (1). Note that empty cells are not counted.
Note
Since the N-1-variance includes Bessel's correction, whereas the N-variance calculated by VARPA or VARP does not, under reasonable conditions the N-1-variance is an unbiased estimator of the variance of the population from which the sample is drawn.
Microsoft Excel Compatibility
This function is Excel compatible.
VARP
Synopsis
VARP(area1,area2,…)
Arguments
area1: first cell area
area2: second cell area
Description
VARP is also known as the N-variance.
VARPA
Synopsis
VARPA(area1,area2,…)
Arguments
area1: first cell area
area2: second cell area
Description
VARPA is also known as the N-variance.
Numbers, text and logical values are included in the calculation too. If the cell contains text or the argument evaluates to FALSE, it is counted as value zero (0). If the argument evaluates to TRUE, it is counted as one (1). Note that empty cells are not counted.
Microsoft Excel Compatibility
This function is Excel compatible.
WEIBULL
Synopsis
WEIBULL(x,alpha,beta,cumulative)
Arguments
x: number
alpha: scale parameter
beta: scale parameter
cumulative: whether to evaluate the density function or the cumulative distribution function
Description
If the cumulative boolean is true it will return: 1 - exp (-(x/beta)^alpha), otherwise it will return (alpha/beta^alpha) * x^(alpha-1) * exp(-(x/beta^alpha)).
Note
If x < 0 this function returns a #NUM! error. If alpha <= 0 or beta <= 0 this function returns a #NUM! error.
Microsoft Excel Compatibility
This function is Excel compatible.
See also
ZTEST
Synopsis
ZTEST(ref,x,stddev)
Arguments
ref: data set (sample)
x: population mean
stddev: population standard deviation, defaults to the sample standard deviation
Description
ZTEST calculates the probability of observing a sample mean as large as or larger than the mean of the given sample for samples drawn from a normal distribution with mean x and standard deviation stddev.
Note
If ref contains less than two data items ZTEST returns #DIV/0! error.
Microsoft Excel Compatibility
This function is Excel compatible.
OpenDocument Format (ODF) Compatibility
This function is OpenFormula compatible.
See also
CONFIDENCE, NORMDIST, NORMINV, NORMSDIST, NORMSINV, STANDARDIZE.