Statistical in Windows Forms Calculation Engine (Calculate)
AVEDEV
Returns the average of the absolute mean deviations of data points. Avedev
is a measure of the variability in a data set.
Syntax
AVEDEV(number1, number2, …)
where:
 number1, number2, … are arguments for which you want the average of the absolute deviations. You can also use a single array or a reference to an array instead of arguments separated by commas.
Remarks:

The arguments must either be numbers or names, arrays or references that contain numbers.

If an array or reference argument contains text, logical values or empty cells, those values are ignored; however, cells with the a zero value are included.
AVERAGE
Returns the average (arithmetic mean) of the arguments.
Syntax
AVERAGE(number1, number2, …)
where:
 number1, number2, … are numeric arguments for which you want the average.
Remarks:

The arguments must either be numbers or names, arrays or references that contain numbers.

If an array or reference argument contains text, logical values, or empty cells, those values are ignored; however, cells with zero value are included.
AVERAGEA
Calculates the average (arithmetic mean) of the values in the list of arguments. In addition to numbers and text logical values such as True and False are also included in the calculation.
Syntax:
AVERAGEA(value1, value2,…)
where:
 value1, value2, … are cells, ranges of cells, or values for which you want the average.
Remarks:

The arguments must be numbers, names, arrays, or references.

Array or reference arguments that contain text evaluate as 0 (zero). If the calculation should not include text values in the average, then use the
AVERAGE
function. 
Arguments that contain
True
evaluate as 1; arguments that containFalse
evaluate as 0 (zero).
AVERAGEIF
The AVERAGEIF
function returns the average of the cells in a specified range which satisfies the given criteria.
Syntax:
AVERAGEIF(range, criteria, [average_range])
where:

range is the cells range to calculate the average value.

criteria are the condition to calculate the average.

average_range is the range optional cells range to computed average. If the average is not included, then the range is used for the average.
AVERAGEIFS
The AVERAGEIFS
returns the average of the cells in a specified range which satisfies the given multiple criteria.
Syntax:
AVERAGEIFS(average_range, criteria_range1, criteria1, [criteria_range2, criteria2], …)
where:

average_range is the range of cells to calculate the average.

criteria_range1 is the first range to calculate the average.

criteria1 is the first condition for the first criteria range.

criteria_range2 is the optional cells range to evaluate the average.

criteria2 is the optional condition for the criteria range 2.
BINOM.DIST
The Binom.Dist
function returns the Binomial Distribution probability for a given number of successes from a specified number of trials.
Syntax:
BINOM.DIST (trial number,sp,value, cumulative)
where:

trial number is the number of Bernoulli trials.

sp is the probability of a success on each trial.

value is the criterion value.

cumulative is a logical value that determines the form of the function.
Remarks:

#NUM!
occurs when trial number is lesser than zero, when sp and value are lesser than zero or greater than one. 
#VALUE!
occurs when trials, sp, and value are nonnumeric.
BETADIST
Returns the cumulative beta probability density function
Syntax:
BETADIST(x,alpha,beta,[A],[B])
Where:

x denotes the value between A and B at which to evaluate the function.

alpha denotes a parameter of the distribution.

beta denotes a parameter of the distribution.

A denotes a lower bound to the interval of x.

B denotes an upper bound to the interval of x.
Remarks:

If any argument is nonnumeric, BETADIST returns the #VALUE! error value.

If alpha ≤ 0 or beta ≤ 0, BETADIST returns the #NUM! error value.

If x < A, x > B, or A = B, BETADIST returns the #NUM! error value.

If you omit values for A and B, BETADIST uses the standard cumulative beta distribution, so that A = 0 and B = 1.
BINOMDIST
Returns the individual term binomial distribution probability
Syntax:
BINOMDIST(number_s,trials,probability_s,cumulative)
Where:

Number_s denotes the number of successes in trials.

Trials denotes the number of independent trials.

Probability_s denotes the probability of success on each trial.

Cumulative denotes a logical value that determines the form of the function. If cumulative is TRUE, then BINOMDIST returns the cumulative distribution function, which is the probability that there are at most number_s successes; if FALSE, it returns the probability mass function, which is the probability that there are number_s successes.
BINOM.INV
The Binom.Inv
function returns the smallest value for which the cumulative binomial distribution is greater than or equal to a criterion value.
Syntax:
BINOM.INV(trial number,sp,value)
Where:

trial number is the number of Bernoulli trials.

sp is the probability of a success on each trial.

value is the criterion value.
Remarks:

#NUM!
 occurs if trial number is less than zero, if sp and value is less than zero or greater one. 
#VALUE!
 occurs if trials, sp and value are nonnumeric.
CHIDIST
The CHIDIST
function returns the righttailed probability of the chisquared distribution.
Syntax:
CHIDIST(x,degFreedom)
Where:

x is the value at which the chisquare distribution is to be evaluated (must be ≥ 0).

degFreedom is the number of degrees of freedom.
Remarks:

#NUM!
 occurs if the x is negative or degFreedom argument is invalid.
CHISQ.TEST
Returns the chisquared statistical test for independence
Syntax:
CHISQ.TEST(actual_range,expected_range)
Where:

actual_range denotes the range of data that contains observations to test against expected values.

expected_range denotes the range of data that contains the ratio of the product of row totals and column totals to the grand total.
CHIINV
Returns the inverse of the righttailed probability of the chisquared distribution
Syntax:
CHIINV(probability,deg_freedom)
Where:

probability denotes a probability associated with the chisquared distribution.

deg_freedom denotes the number of degrees of freedom.
Remarks:

If either argument is nonnumeric, CHIINV returns the #VALUE! error value.

If probability < 0 or probability > 1, CHIINV returns the #NUM! error value.

If deg_freedom is not an integer, it is truncated.

If deg_freedom < 1, CHIINV returns the #NUM! error value.
CONFIDENCE.NORM
The Confidence.Norm
function uses Normal Distribution to calculate a confidence value that can be used to construct the confidence interval for a population mean, for a supplied probability, and sample size.
Syntax:
CONFIDENCE.NORM(alpha,stdev,size)
where:

alpha is the significance level.

stdev is the population standard deviation for the data range.

size is the sample size.
Remarks:

#VALUE!
occurs when any argument is nonnumeric. 
#NUM!
occurs when alpha and stdev is lesser than or equal to zero or when alpha is greater than or equal to zero. 
#DIV/0!
occurs when the size is equal to one.
CONFIDENCE.T
Returns the confidence interval for a population mean
Syntax:
CONFIDENCE.T(alpha,standard_dev,size)
Where:

alpha denotes the significance level used to compute the confidence level. The confidence level equals 100*(1  alpha)%, or in other words, an alpha of 0.05 indicates a 95 percent confidence level.

standard_dev denotes the population standard deviation for the data range and is assumed to be known.

size denotes the sample size.
Remarks:

If any argument is nonnumeric, CONFIDENCE.T returns the #VALUE! error value.

If alpha ≤ 0 or alpha ≥ 1, CONFIDENCE.T returns the #NUM! error value.

If standard_dev ≤ 0, CONFIDENCE.T returns the #NUM! error value.

If size is not an integer, it is truncated.

If size equals 1, CONFIDENCE.T returns #DIV/0! error value
CHISQ.INV
The Chisq.Inv
function returns the inverse of the lefttailed probability of the chisquared distribution.
Syntax:
CHISQ.INV(probability,degFreedom)
where:

probability is a probability of chisquared distribution.

degFreedom is the number of degrees of freedom.
Remarks:

#NUM!
occurs when probability is lesser than zero, when probability is greater than 1, and degFreedom is lesser than 1. 
#VALUE!
occurs when probability or degFreedom is nonnumeric.
CHISQ.INV.RT
The Chisq.Inv.Rt
function calculates the inverse of the righttailed probability of the chisquare distribution.
Syntax:
CHISQ.INV.RT(probability, degFreedom)
where:

probability is a probability of chisquared distribution.

degFreedom is the number of degrees of freedom.
Remarks:

#NUM!
occurs when probability is lesser than zero, when probability is greater than 1, and when degFreedom is lesser than 1. 
#VALUE!
occurs when probability or degFreedom is nonnumeric.
CHISQ.DIST.RT
The Chisq.Dist.Rt
function calculates the righttailed probability of the chisquare distribution.
Syntax:
CHISQ.DIST.RT(x,degFreedom)
where:

x is the value that evaluates the function.

degFreedom is the number of degrees of freedom.
Remarks:

#VALUE!
occurs when either argument is nonnumeric. 
#VALUE!
occurs when any argument is nonnumeric. 
#NUM!
occurs when f degFreedom < 1 or degFreedom >10^10.
CHISQ.DIST
The Chisq.Dist
function calculates the Probability Density Function or the Cumulative Distribution Function for the chisquare distribution.
Syntax:
CHISQ.DIST(x,degFreedom,cumulative)
where:

x is the value that evaluates the function.

degFreedom is the number of degrees of freedom.

cumulative is a logical value that determines the form of the function.
Remarks:

#VALUE!
 occurs if any argument is nonnumeric. 
#NUM!
 occurs if x is negative and if f degFreedom < 1 or degFreedom >10^10.
CONFIDENCE
Returns the confidence interval for a population mean, using a normal distribution
Syntax:
CONFIDENCE(alpha,standard_dev,size)
Where:

alpha denotes the significance level used to compute the confidence level. The confidence level equals 100*(1  alpha)%, or in other words, an alpha of 0.05 indicates a 95 percent confidence level.

standard_dev denotes the population standard deviation for the data range and is assumed to be known.

size denotes the sample size.
CORREL
The Correl
function returns the correlation coefficient of the array1 and array2 cell ranges.
Syntax:
CORREL(array1, array2)
where:

array1 is a cell range of values.

array2 is the second cell range of values.
Remarks:
array1 and array2 must have the same number of data points.
COUNT
The Count
counts the number of items in a list that contains numbers.
Syntax:
COUNT(value1, value2,…)
where:
value1, value2, … are arguments that can contain or refer to a variety of different types of data, but only numbers are counted.
Remarks:

Arguments that are numbers, dates or text representations of numbers are counted; arguments that are error values or text that cannot be translated into numbers are ignored.

If an argument is an array or reference, only numbers in that array or reference are counted. Empty cells, logical values, text or error values in the array or reference are ignored.
COUNTA
The CountA
counts the number of cells that are not empty.
Syntax:
COUNTA(value1, value2,…)
where:
 value1, value2, … are arguments representing the values you want to count. In this case, a value is any type of information, excluding empty cells.
COUNTBlank
The CountBlank
counts empty cells in a specified range of cells.
Syntax:
COUNTBLANK(range)
where:
range is the range from which you want to count the blank cells.
Remarks:
Cells with formulas that return “” (empty text) are also counted. Cells with zero values are not counted.
COUNTIF
Returns the number of cells (of a supplied range), that satisfy a given criteria.
Syntax:
COUNTIF (range, criteria)
where:

range is the range of cells to count.

criteria is the criteria that controls which cells should be counted.
COUNTIFS
Returns the number of cells (of a supplied range), that satisfy a set of given criteria
Syntax:
COUNTIFS(criteria_range1, criteria1, [criteria_range2, criteria2]…)
Where:

criteria_range1 denotes the first range in which to evaluate the associated criteria.

criteria1 denotes the criteria in the form of a number, expression, cell reference, or text that define which cells will be counted. For example, criteria can be expressed as 32, “>32”, B4, “apples”, or “32”.

criteria_range2, criteria2, … is additional ranges and their associated criteria. Up to 127 range/criteria pairs are allowed.
Remarks:

Each range’s criteria is applied one cell at a time. If all of the first cells meet their associated criteria, the count increases by 1. If all of the second cells meet their associated criteria, the count increases by 1 again, and so on until all of the cells are evaluated.

If the criteria argument is a reference to an empty cell, the COUNTIFS function treats the empty cell as a 0 value.

You can use the wildcard characters— the question mark (?) and asterisk (*) — in criteria. A question mark matches any single character, and an asterisk matches any sequence of characters. If you want to find an actual question mark or asterisk, type a tilde (~) before the character.
COVAR
Returns population covariance (i.e. the average of the products of deviations for each pair within two supplied data sets)
Syntax:
COVAR(array1,array2)
Where:

array1 is the first cell range of integers.

array2 is the second cell range of integers.
COVARIANCE.P
Returns population covariance, the average of the products deviation for each data point pair in two data sets.
Syntax:
COVARIANCE.P(array1,array2)
Where:

array1 denotes the first cell range of integers.

array2 denotes the second cell range of integers.
COVARIANCE.S
Returns the sample covariance, the average of the products deviation for each data point pair in two data sets.
Syntax:
COVARIANCE.S(array1,array2)
Where:

Array1 denotes the first cell range of integers.

Array2 denotes the second cell range of integers.
CRITBINOM
Returns the smallest value for which the cumulative binomial distribution is greater than or equal to a criterion value
Syntax:
CRITBINOM(trials,probability_s,alpha)
Where:

Trials denotes the number of Bernoulli trials.

Probability_s denotes the probability of a success on each trial.

Alpha denotes the criterion value.
Remarks:

If any argument is nonnumeric, CRITBINOM returns the #VALUE! error value.

If trials is not an integer, it is truncated.

If trials < 0, CRITBINOM returns the #NUM! error value.

If probability_s is < 0 or probability_s > 1, CRITBINOM returns the #NUM! error value.

If alpha < 0 or alpha > 1, CRITBINOM returns the #NUM! error value
DEVSQ
The DevSQ
returns the sum of squares of deviations of data points from their sample mean.
Syntax:
DEVSQ(number1, number2,…)
where:
number1, number2, … are arguments for which, you want to calculate the sum of squared deviations. You can also use a single array or a reference to an array instead of arguments separated by commas.
Remarks:
The arguments must be numbers or names, arrays or references that contain numbers.
EXPON.DIST
The Expon.Dist
function calculates the value of the probability density function or the cumulative distribution function for the Exponential Distribution.
Syntax:
EXPON.DIST(x,y,cumulative)
where:

x is the value that evaluates the function.

y is the parameter value.

cumulative is a logical value for given function.
Remarks:

#NUM!
occurs when x is lesser than zero and y is equal to or lesser than zero. 
#VALUE!
occurs when x or y is nonnumeric.
EXPONDIST
Returns the exponential distribution
Syntax:
EXPONDIST(x,lambda,cumulative)
Where:

x denotes the value of the function.

lambda denotes the parameter value.

cumulative denotes a logical value that indicates which form of the exponential function to provide. If cumulative is TRUE, EXPONDIST returns the cumulative distribution function; if FALSE, it returns the probability density function.
F.DIST
The F.Dist
function calculates the Probability Density Function or the Cumulative Distribution Function for the F Distribution.
Syntax:
F.DIST(x,degFreedom1,degFreedom2,cumulative)
where:

x is the value that evaluates the function.

degFreedom1 is the numerator degree of freedom.

degFreedom1 is the denominator degree of freedom.

cumulative is a logical value that determines the form of the function.
Remarks:

#VALUE!
occurs when any argument is nonnumeric. 
#NUM!
occurs when x is negative, when degFreedom1< 1 and when degFreedom1< 1
F.DIST.RT
The F.Dist.Rt
function calculates the F Probability Distribution that measures the degree of diversity between two data sets.
Syntax:
F.DIST.RT(x, degFreedom1, degFreedom2)
where:

x is the value that evaluates the function.

degFreedom1 is the numerator degree of freedom.

degFreedom2 is the denominator degree of freedom.
Remarks:

#VALUE!
occurs when any argument is nonnumeric. 
#NUM!
occurs when x is negative, when degFreedom1< 1 and when degFreedom2< 1.
F.INV.RT
The F.INV.RT
function calculates the inverse of the Cumulative F Distribution for a supplied probability.
Syntax:
F.INV.RT(probability,degFreedom1,degFreedom2)
where:

probability is a probability that corresponds to the normal distribution.

degFreedom1 is the numerator degrees of freedom.

degFreedom2 is the denominator degrees of freedom.
Remarks:

#NUM!
occurs when probability is equal to or lesser than zero and when probability is equal to or greater than one. 
#VALUE!
occurs when probability or degFreedom1 or degFreedom2 is nonnumeric.
FDIST
Returns the F probability distribution (probability density or cumulative distribution function)
Syntax:
FDIST(x,deg_freedom1,deg_freedom2)
Where:

x denotes the value at which to evaluate the function.

deg_freedom1 denotes the numerator degrees of freedom.

deg_freedom2 denotes the denominator degrees of freedom.
Remarks:

If any argument is nonnumeric, FDIST returns the #VALUE! error value.

If x is negative, FDIST returns the #NUM! error value.

If deg_freedom1 or deg_freedom2 is not an integer, it is truncated.

If deg_freedom1 < 1 or deg_freedom1 ≥ 1010, FDIST returns the #NUM! error value.

If deg_freedom2 < 1 or deg_freedom2 ≥ 1010, FDIST returns the #NUM! error value.

FDIST is calculated as FDIST=P( F>x ), where F is a random variable that has an F distribution with deg_freedom1 and deg_freedom2 degrees of freedom.
FINV
Returns the inverse of the righttailed F probability distribution for two data sets
Syntax:
FINV(probability,deg_freedom1,deg_freedom2)
Where:

Probability denotes a probability associated with the F cumulative distribution.

Deg_freedom1 denotes the numerator degrees of freedom.

Deg_freedom2 denotes the denominator degrees of freedom.
FISHER
The Fisher
returns the Fisher transformation at x. This transformation produces a function that is normally distributed rather than skewed.
Syntax:
FISHER(x)
where:
x is a numeric value for which you want the transformation.
Remarks:
x must be > 1 and < 1.
FISHERInv
The FisherInv
returns the inverse of the Fisher transformation. If y = FISHER(x), then FISHERINV(y) = x.
Syntax:
FISHERINV(y)
where:
y is the value for which you want to perform the inverse of the transformation.
FORECAST
The Forecast
calculates a future value by using existing values in a linear regression. The predicted value is a yvalue for a given xvalue.
Syntax:
FORECAST(x, known_ys, known_xs)
where:

x is the data point for which you want to predict a value.

known_ys is the dependent array or range of data.

known_xs is the independent array or range of data.
F.DIST.RT
The F.DIST.RT
function calculates the F Probability Distribution, which measures the degree of diversity between two data sets.
Syntax:
F.DIST.RT(x, degFreedom1, degFreedom2)
where:

x is the value that evaluates the function.

degFreedom1 is the numerator degrees of freedom.

DegFreedom2 is the denominator degrees of freedom.
Remarks:

#VALUE!
occurs if any argument is nonnumeric. 
#NUM!
occurs if x is negative, if degFreedom1< 1 and if degFreedom2< 1
GEOMEAN
The Geomean
returns the geometric mean of an array or range of positive data.
Syntax:
GEOMEAN(number1, number2,…)
where:
number1, number2, … are arguments for which you want to calculate the mean.
Remarks:

The arguments must be either numbers or names, arrays or references that contain numbers.

All values must be positive.
HARMEAN
The Harmean
returns the harmonic mean of a data set. The harmonic mean is the reciprocal of the arithmetic mean of reciprocals.
Syntax:
HARMEAN(number1, number2,…)
where:
number1, number2, … are arguments for which you want to calculate the mean.
Remarks:

The arguments must be either numbers or names, arrays or references that contain numbers.

All data values must be positive.
INTERCEPT
The Intercept
calculates the point at which, the least squares fit line will intersect the yaxis.
Syntax:
INTERCEPT(known_y’s, known_x’s)
where:

known_y’s is the dependent set of observations or data.

known_x’s is the independent set of observations or data.
LARGE
The Large
returns the kth largest value in a data set.
Syntax:
LARGE(array, k)
where:

array is the array or range of data for which, you want to determine the kth largest value.

k is the position (from the largest) in the array or cell range of data to return.
Remarks:
If n is the number of data points in a range, then LARGE(array,1) returns the largest value, and LARGE(array,n)
returns the smallest value.
MAX
The Max
returns the largest value in a set of values.
Syntax:
MAX(number1, number2, …)
where:
number1, number2, … are numbers for which you want to find the maximum value.
MAXA
The Maxa
returns the largest value in a list of arguments. Text and logical values such as True and False are compared as well as numbers.
Syntax:
MAXA(value1, value2, …)
where:
 value1, value2, … are values for which you want to find the largest value.
Remarks:

You can specify arguments that are numbers, empty cells, logical values or text representations of numbers. Arguments that are error values cause errors. If the calculation does not include text or logical values, use the MAX worksheet function instead.

If an argument is an array or reference, only values in that array or reference are used. Empty cells and text values in the array or reference are ignored.

Arguments that contain True evaluate as 1; arguments that contain text or False evaluate as 0 (zero).

If the arguments contain no values, MAXA returns 0 (zero).
MEDIAN
The Median
returns the median of the given numbers. The median is the number in the middle of a set of numbers; that is, half the numbers have values that are greater than the median and half have values that are less.
Syntax:
MEDIAN(number1, number2, …)
where:
number1, number2, … are numbers for which you want the median.
Remarks:
If there is an even number of numbers in the set, then MEDIAN calculates the average of the two numbers in the middle.
MIN
The Min
returns the smallest number in a set of values.
Syntax:
MIN(number1, number2, …)
where:
number1, number2, … are numbers for which you want to find the minimum value.
Remarks:
If an argument is an array or reference, only numbers in that array or reference are used. Empty cells, logical values or text in the array or reference are ignored. If logical values and text should not be ignored, use MINA.
MINA
The Mina
returns the smallest value in the list of arguments. Text and logical values such as True and False are compared as well as numbers.
Syntax:
MINA(value1, value2, …)
where:
value1, value2, … are values for which, you want to find the smallest value.
Remarks:
Arguments that contain True evaluate as 1; arguments that contain text or False evaluate as 0 (zero).
NORM.DIST
The NORM.DIST
function calculates the normal distribution for a supplied value of x, and a supplied distribution mean & standard deviation.
Syntax:
NORM.DIST(x,mean,stdev,cumulative)
where:

x is the value for which you want the distribution.

mean is the arithmetic mean of the distribution.

stdev is the standard deviation of the distribution.

cumulative is a logical value for given function.
Remarks:

#VALUE!
occurs if mean or stdev is nonnumeric. 
#NUM!
occurs if stdev is equal to or less than zero.
NORMDIST
Returns the normal cumulative distribution
Syntax:
NORMDIST(x,mean,standard_dev,cumulative)
where:

x is the value for which you want the distribution.

mean is the arithmetic mean of the distribution.

standard_dev is the standard deviation of the distribution.

cumulative is a logical value that determines the form of the function. If cumulative is TRUE, NORMDIST returns the cumulative distribution function; if FALSE, it returns the probability mass function.
Remarks:

#VALUE!
Occurs when mean or standard_dev is nonnumeric. 
#NUM!
Occurs when standard_dev ≤ 0. 
If mean = 0, standard_dev = 1, and cumulative = TRUE, NORMDIST returns the standard normal distribution, NORMSDIST.
NORMSDIST
Returns the standard normal cumulative distribution.
Syntax:
NORMSDIST(z)
where:
 z is the value for which you want the distribution.
Remarks:

#VALUE!
Occurs when z is nonnumeric.
GAMMA.INV
The Gamma.Inv
function returns the inverse of the Gamma Distribution.
Syntax:
GAMMA.INV(x,y,z,cumulative)
where:

x is the value that evaluates the function.

y is a distribution parameter.

z is a distribution parameter.

cumulative is a logical value that indicates which form of the exponential function to provide.
Remarks:

#NUM!
occurs when x is lesser than zero, when z is equal to or lesser than zero and occurs when alpha is equal to or lesser than zero. 
#VALUE!
occurs when x or y or z is nonnumeric.
GAMMA.DIST
Returns the gamma distribution
Syntax:
GAMMA.DIST(x,alpha,beta,cumulative)
Where:

x denotes the value at which you want to evaluate the distribution.

alpha denotes a parameter to the distribution.

beta denotes a parameter to the distribution. If beta = 1, GAMMA.DIST returns the standard gamma distribution.

cumulative denotes a logical value that determines the form of the function. If cumulative is TRUE, GAMMA.DIST returns the cumulative distribution function; if FALSE, it returns the probability density function.
GAMMADIST
Returns the gamma distribution
Syntax:
GAMMADIST(x,alpha,beta,cumulative)
Where:

x denotes the value at which you want to evaluate the distribution.

alpha denotes a parameter to the distribution.

beta denotes a parameter to the distribution. If beta = 1, GAMMADIST returns the standard gamma distribution.

cumulative denotes a logical value that determines the form of the function. If cumulative is TRUE, GAMMADIST returns the cumulative distribution function; if FALSE, it returns the probability density function.
GAMMAINV
Returns the inverse gamma cumulative distribution
Syntax:
GAMMAINV(probability,alpha,beta)
Where:

probability denotes the probability associated with the gamma distribution.

alpha denotes a parameter to the distribution.

beta denotes a parameter to the distribution. If beta = 1, GAMMAINV returns the standard gamma distribution.
Remarks:

If any argument is text, GAMMAINV returns the #VALUE! error value.

If probability < 0 or probability > 1, GAMMAINV returns the #NUM! error value.

If alpha ≤ 0 or if beta ≤ 0, GAMMAINV returns the #NUM! error value.
GAMMALN
Calculates the natural logarithm of the gamma function for a supplied value
Syntax:
GAMMALN(x)
Where:
x denotes the value for which you want to calculate GAMMALN
.
GAMMALN.PRECISE
The Gammaln.Precise
function returns the natural logarithm of the Gamma Distribution.
Syntax:
GAMMALN.PRECISE(x)
where:
 x is the positive numeric value that evaluates the function.
Remarks:

#NUM!
occurs when x is lesser than zero. 
#VALUE!
occurs when x is nonnumeric.
GROWTH
Returns numbers in a exponential growth trend, based on a set of supplied x and y values
Syntax:
GROWTH(known_y’s, [known_x’s], [new_x’s], [const])
Where:

Known_y’s denotes the set of yvalues you already know in the relationship
y = b*mx
.
If the array known_y’s is in a single column, then each column of known_x’s is interpreted as a separate variable.

If the array known_y’s is in a single row, then each row of known_x’s is interpreted as a separate variable.

If any of the numbers in known_y’s is 0 or negative, GROWTH returns the #NUM! error value.


Known_x’s denotes an optional set of xvalues that you may already know in the relationship
y = b*mx
.
The array known_x’s can include one or more sets of variables. If only one variable is used, known_y’s and known_x’s can be ranges of any shape, as long as they have equal dimensions. If more than one variable is used, known_y’s must be a vector (that is, a range with a height of one row or a width of one column).

If known_x’s is omitted, it is assumed to be the array {1,2,3,…} that is the same size as known_y’s.


New_x’s denotes are new xvalues for which you want GROWTH to return corresponding yvalues.

New_x’s must include a column (or row) for each independent variable, just as known_x’s does. So, if known_y’s is in a single column, known_x’s and new_x’s must have the same number of columns. If known_y’s is in a single row, known_x’s and new_x’s must have the same number of rows.

If new_x’s is omitted, it is assumed to be the same as known_x’s.

If both known_x’s and new_x’s are omitted, they are assumed to be the array {1,2,3,…} that is the same size as known_y’s.


Const denotes a logical value specifying whether to force the constant b to equal 1.

If const is TRUE or omitted, b is calculated normally.

If const is FALSE, b is set equal to 1 and the mvalues are adjusted so that
y = mx
.

Remarks:

Formulas that return arrays must be entered as array formulas after selecting the correct number of cells.

When entering an array constant for an argument such as known_x’s, use commas to separate values in the same row and semicolons to separate rows.
HYPGEOMDIST
Returns the hypergeometric distribution
Syntax:
HYPGEOMDIST(sample_s,number_sample,population_s,number_pop)
Where:

Sample_s denotes the number of successes in the sample.

Number_sample denotes the size of the sample.

Population_s denotes tThe number of successes in the population.

Number_pop denotes the population size.
HYPGEOM.DIST
Returns the hypergeometric distribution
Syntax:
HYPGEOM.DIST(sample_s,number_sample,population_s,number_pop,cumulative)
Where:

sample_s denotes the number of successes in the sample.

number_sample denotes the size of the sample.

population_s denotes the number of successes in the population.

number_pop denotes the population size.

cumulative denotes a logical value that determines the form of the function. If cumulative is TRUE, then HYPGEOM.DIST returns the cumulative distribution function; if FALSE, it returns the probability mass function.
KURT
Returns the kurtosis of a data set
Syntax:
KURT(number1, [number2], …)
where:
 number1, number2, … Number1 is required, subsequent numbers are optional. 1 to 255 arguments for which you want to calculate kurtosis. You can also use a single array or a reference to an array instead of arguments separated by commas.
LOGEST
Returns the parameters of an exponential trend for a supplied set of x and y values
Syntax:
LOGEST(known_y’s, [known_x’s], [const], [stats])
Where:

Known_y’s denotes the set of yvalues you already know in the relationship
y = b*mx
.
If the array known_y’s is in a single column, then each column of known_x’s is interpreted as a separate variable.

If the array known_y’s is in a single row, then each row of known_x’s is interpreted as a separate variable.


Known_x’s denotes an optional set of xvalues that you may already know in the relationship y = b*mx.

The array known_x’s can include one or more sets of variables. If only one variable is used, known_y’s and known_x’s can be ranges of any shape, as long as they have equal dimensions. If more than one variable is used, known_y’s must be a range of cells with a height of one row or a width of one column (which is also known as a vector).

If known_x’s is omitted, it is assumed to be the array {1,2,3,…} that is the same size as known_y’s.


Const denotes a logical value specifying whether to force the constant b to equal 1.

If const is TRUE or omitted, b is calculated normally.

If const is FALSE, b is set equal to 1, and the mvalues are fitted to
y = mx
.


Stats denotes a logical value specifying whether to return additional regression statistics.

If stats is TRUE, LOGEST returns the additional regression statistics, so the returned array.

If stats is FALSE or omitted, LOGEST returns only the mcoefficients and the constant b.

LOGINV
Returns the inverse of the lognormal distribution
Syntax:
LOGINV(probability, mean, standard_dev)
Where:

probability denotes a probability associated with the lognormal distribution.

mean denotes the mean of ln(x).

standard_dev denotes the standard deviation of ln(x).
LOGNORMDIST
Returns the cumulative lognormal distribution
Syntax:
LOGNORMDIST(x,mean,standard_dev)
Where:

x denotes the value at which to evaluate the function.

mean denotes the mean of ln(x).

standard_dev denotes the standard deviation of ln(x).
LOGNORM.DIST
The Lognorm.Dist
function calculates the LogNormal Probability Density Function or the Cumulative LogNormal Distribution Function for a supplied value of x.
Syntax:
LOGNORM.DIST(x,mean,stdev,cumulative)
where:

x is the value that evaluates the function.

mean is the mean value of ln(x).

stdev is the standard deviation of ln(x).

cumulative is a logical value that determines the form of the function.
Remarks:

#VALUE!
occurs when any argument is nonnumeric. 
#NUM!
occurs when x ≤ 0 or if stdev ≤ 0.
LOGNORM.INV
The Lognorm.Inv
function calculates the inverse of the Cumulative LogNormal Distribution Function of x for a supplied probability.
Syntax:
LOGNORM.INV(probability, mean, stdev)
where:

probability is a probability that corresponds to the lognormal distribution.

mean is the arithmetic mean of In(x).

stdev is the standard deviation of ln(x).
Remarks:

#VALUE!
occurs when any argument is nonnumeric. 
#NUM!
occurs when probability <= 0 or probability >= 1 and if Stdev<=0.
MAXIFS
Returns the largest value from a subset of values in a list that are specified according to one or more criteria
Syntax:
MAXIFS(max_range, criteria_range1, criteria1, [criteria_range2, criteria2], …)
Where:

max_range denotes the actual range of cells in which the maximum will be determined.

criteria_range1 is the set of cells to evaluate with the criteria.

criteria1 is the criteria in the form of a number, expression, or text that defines which cells will be evaluated as maximum. The same set of criteria works for the MINIFS, SUMIFS, and AVERAGEIFS functions.

criteria_range2,criteria2, … is additional ranges and their associated criteria. You can enter up to 126 range/criteria pairs.
Remarks:
The size and shape of the max_range and criteria_rangeN arguments must be the same, otherwise these functions return the #VALUE! error.
MINIFS
Returns the smallest value from a subset of values in a list that are specified according to one or more criteria
Syntax:
MINIFS(min_range, criteria_range1, criteria1, [criteria_range2, criteria2], …)
Where:

min_range denotes the actual range of cells in which the minimum value will be determined.

criteria_range1 is the set of cells to evaluate with the criteria.

criteria1 is the criteria in the form of a number, expression, or text that defines which cells will be evaluated as minimum. The same set of criteria works for the MAXIFS, SUMIFS and AVERAGEIFS functions.

criteria_range2,criteria2, … is additional ranges and their associated criteria.You can enter up to 126 range/criteria pairs.
Remark:
The size and shape of the min_range and criteria_rangeN arguments must be the same, otherwise these functions return the #VALUE! error.
MODE
Returns the Mode (the most frequently occurring value) of a list of supplied numbers
Syntax:
MODE(number1,[number2],…)
Where:

number1 denotes the first number argument for which you want to calculate the mode.

number2,… is number arguments 2 to 255 for which you want to calculate the mode. You can also use a single array or a reference to an array instead of arguments separated by comma
MODE.MULT
Returns a vertical array of the most frequently occurring values in an array or range of data
Syntax:
MODE.MULT((number1,[number2],…)
Where:

number1 denotes the first number argument for which you want to calculate the mode.

number2, … denotes number arguments 2 to 254 for which you want to calculate the mode. You can also use a single array or a reference to an array instead of arguments separated by commas.
Remarks:

Arguments can either be numbers or names, arrays, or references that contain numbers.

If an array or reference argument contains text, logical values, or empty cells, those values are ignored; however, cells with the value zero are included.

Arguments that are error values or text that cannot be translated into numbers cause errors.

If the data set contains no duplicate data points, MODE.MULT returns the #N/A error value
MODE.SNGL
Returns the Mode (the most frequently occurring value) of a list of supplied numbers
Syntax:
MODE.SNGL(number1,[number2],…)
Where:

number1 denotes the first argument for which you want to calculate the mode.

number2, … denotes arguments 2 to 254 for which you want to calculate the mode. You can also use a single array or a reference to an array instead of arguments separated by commas.
NEGBINOMDIST
Returns the negative binomial distribution
Syntax:
NEGBINOMDIST(number_f,number_s,probability_s)
Where:
 number_f is the number of failures.
 number_s is the threshold number of successes.
 probability_s is the probability of a success.
NORMINV
Returns the inverse of the normal cumulative distribution
Syntax:
NORMINV(probability,mean,standard_dev)
Where:

probability denotes a probability corresponding to the normal distribution.

mean denotes the arithmetic mean of the distribution.

standard_dev denotes the standard deviation of the distribution.
Remarks:

If any argument is nonnumeric, NORMINV returns the #VALUE! error value.

If probability <= 0 or if probability >= 1, NORMINV returns the #NUM! error value.

If standard_dev ≤ 0, NORMINV returns the #NUM! error value.

If mean = 0 and standard_dev = 1, NORMINV uses the standard normal distribution (see NORMSINV).
NORMSINV
Returns the inverse of the standard normal cumulative distribution
Syntax
NORMSINV(probability)
Where:
probability denotes a probability corresponding to the normal distribution.
Remarks:

If Probability is nonnumeric, NORMSINV returns the #VALUE! error value.

If Probability <= 0 or if Probability >= 1, NORMSINV returns the #NUM! error value.
NORM.INV
Returns the inverse of the normal cumulative distribution
Syntax:
NORM.INV(probability,mean,standard_dev)
Where:

probability denotes a probability corresponding to the normal distribution.

mean denotes the arithmetic mean of the distribution.

standard_dev denotes the standard deviation of the distribution.
Remarks:

If any argument is nonnumeric, NORM.INV returns the #VALUE! error value.

If probability <= 0 or if probability >= 1, NORM.INV returns the #NUM! error value.

If standard_dev ≤ 0, NORM.INV returns the #NUM! error value.

If mean = 0 and standard_dev = 1, NORM.INV uses the standard normal distribution (see NORMS.INV).
NORM.S.DIST
The Norm.S.Dist
function returns the standard normal distribution.
Syntax:
NORM.S.DIST(val, cumulative)
where:

val is the value for which you want the distribution.

cumulative is a logical value that determines the form of the function.
NORM.S.INV
The Norm.S.Inv
function returns the inverse of the standard normal cumulative distribution.
Syntax:
NORM.S.INV(probability)
where:
probability is a probability that corresponds to the normal distribution.
NEGBINOM.DIST
The Negbinom.Dist
function calculates the probability mass function or the cumulative distribution function for the Negative Binomial Distribution
.
Syntax:
NEGBINOM.DIST(F_number,S_number,S_probability,cumulative)
where:

F_number is the number of failures.

S_number is the threshold number of successes.

S_probability is the probability of a success.

cumulative is a logical value that determines the form of the function.
PEARSON
Returns the Pearson product moment correlation coefficient
Syntax:
PEARSON(array1, array2)
Where:

array1 denotes a set of independent values.

array2 denotes a set of dependent values.
PERCENTILE
Returns the K’th percentile of values in a supplied range, where K is in the range 0  1 (inclusive)
Syntax:
PERCENTILE(array,k)
Where:

array denotes the array or range of data that defines relative standing.

k denotes the percentile value in the range 0..1, inclusive.
Remarks:

If k is nonnumeric, PERCENTILE returns the #VALUE! error value.

If k is < 0 or if k > 1, PERCENTILE returns the #NUM! error value.

If k is not a multiple of 1/(n  1), PERCENTILE interpolates to determine the value at the kth percentile.
PERCENTILE.EXC
The Percentile.Exc
function returns the kth percentile of values in a range, where k is in the range of 0 to 1 exclusively.
Syntax:
PERCENTILE.EXC(array, k)
where:

array is the range of data that defines relative standing.

k is the percentile value in the range of 0 to 1.
Remarks:

#NUM!
occurs when k is equal to or lesser than zero, when k is equal to or greater than 1, and when the array is empty. 
#VALUE!
occurs when k is nonnumeric.
PERCENTILE.INC
The Percentile.Inc
function returns the kth percentile of values in a range, where k is in the range 0 to 1.
Syntax:
PERCENTILE.INC (array,k)
where:

array is the range of data that defines relative standing.

k is the percentile value in the range 0 to 1.
Remarks:

#NUM!
occurs when k is equal to or lesser than zero, when k is equal to or greater than 1, and when the array is empty. 
#VALUE!
occurs when k is a nonnumeric.
PERCENTILERANK
Returns the rank of a value in a data set, as a percentage (0  1 inclusive)
Syntax:
PERCENTRANK(array,x,[significance])
Where:

array denotes the array or range of data with numeric values that defines relative standing.

x denotes the value for which you want to know the rank.

significance denotes a value that identifies the number of significant digits for the returned percentage value. If omitted, PERCENTRANK uses three digits (0.xxx).
Remarks:

If array is empty, PERCENTRANK returns the #NUM! error value.

If significance < 1, PERCENTRANK returns the #NUM! error value.

If x does not match one of the values in array, PERCENTRANK interpolates to return the correct percentage rank.
PERCENTRANK.EXC
Returns the rank of value in dataset as a percentage of the data set as percentage (0….1, exclusive) of the dataset
Syntax:
PERCENTRANK.EXC(array,x,[significance])
Where:

array denotes the array or range of data with numeric values that defines relative standing

x denotes the value for which you want to know the rank.

significance denotes a value that identifies the number of significant digits for the returned percentage value. If omitted, PERCENTRANK.EXC uses three digits (0.xxx).
Remarks:

If array is empty, PERCENTRANK.EXC returns the #NUM! error value.

If significance < 1, PERCENTRANK.EXC returns the #NUM! error value.

If x does not match one of the values in array, PERCENTRANK.EXC interpolates to return the correct percentage rank.
PERCENTRANK.INC
Returns the rank of value in dataset as a percentage of the data set as percentage (0….1, inclusive) of the dataset
Syntax:
PERCENTRANK.INC(array,x,[significance])
Where:

array denotes the array or range of data with numeric values that defines relative standing.

x denotes the value for which you want to know the rank.

significance denotes a value that identifies the number of significant digits for the returned percentage value. If omitted, PERCENTRANK.INC uses three digits (0.xxx).

bytes specify the number of characters
PERMUT
The Permut
returns the number of permutations for a given number of objects that can be selected from a number of objects.
Syntax:
PERMUT(number, number_chosen)
where:

number is an integer that describes the number of objects.

number_chosen is an integer that describes the number of objects in each permutation.
Remarks:

Number must be > 0 and number_chosen must be >= 0.

Number must be >= number_chosen.
PERMUTATIONA
The PermutationA
function returns the number of permutations for a given number of objects (with repetitions) that can be selected from the total number of objects.
Syntax:
PERMUTATIONA(number, numberchosen)
where:

number is an integer that describes the total number of objects.

numberchosen is an integer that describes the number of objects in each permutation.
Remarks:

#VALUE!
occurs when numeric arguments use data types that are nonnumeric. 
#NUM!
occurs when numeric arguments have values that are not valid.
POISSON
Returns the Poisson distribution
Syntax:
POISSON(x,mean,cumulative))
Where:

x denotes the number of events.

mean denotes the expected numeric value.

cumulative denotes a logical value that determines the form of the probability distribution returned. If cumulative is TRUE, POISSON returns the cumulative Poisson probability that the number of random events occurring will be between zero and x inclusive; if FALSE, it returns the Poisson probability mass function that the number of events occurring will be exactly x.
POISSON.DIST
The Poisson.Dist
function calculates the Poisson Probability Mass Function or the Cumulative Poisson Probability Function for a supplied set of parameters.
Syntax:
POISSON.DIST(x,mean,cumulative)
where:

x is the number of events.

mean is the expected numeric value.

cumulative is a logical value that determines the form of the probability distribution returned.
Remarks:

#VALUE!
occurs when x is not an integer. 
#NUM!
occurs when x or mean is nonnumeric and s when x < 0.
PROB
Returns the probability that values in a supplied range are within given limits.
Syntax:
PROB(x_range, prob_range, [lower_limit], [upper_limit])
Where:

x_range is the range of numeric values of x with which there are associated probabilities.

prob_range denotes a set of probabilities associated with values in x_range.

lower_limit is the lower bound on the value for which you want a probability.

upper_limit is the optional upper bound on the value for which you want a probability.
Remarks:

If any value in prob_range ≤ 0 or if any value in prob_range > 1, PROB returns the #NUM! error value.

If the sum of the values in prob_range is not equal to 1, PROB returns the #NUM! error value.

If upper_limit is omitted, PROB returns the probability of being equal to lower_limit.

If x_range and prob_range contain a different number of data points, PROB returns the #N/A error value.
QUARTILE
Returns the specified quartile of a set of supplied numbers, based on percentile value 0  1 (inclusive)
Syntax:
QUARTILE(array,quart)
Where:

array denotes the array or cell range of numeric values for which you want the quartile value.

quart indicates which value to return.

bytes specify the number of characters
If quart equals  QUARTILE returns 

0  Minimum value. 
1  First quartile (25th percentile) 
2  Median value (50th percentile). 
3  Third quartile (75th percentile. 
4  Maximum value. 
QUARTILE.EXC
Returns the specified quartile of a set of supplied numbers, based on percentile value 0  1 (exclusive)
Syntax:
QUARTILE.EXC(array, quart)
Where:

array denotes the array or cell range of numeric values for which you want the quartile value.

quart indicates which value to return.
Remarks:

If array is empty, QUARTILE.EXC returns the #NUM! error value.

If quart is not an integer, it is truncated.

If quart ≤ 0 or if quart ≥ 4, QUARTILE.EXC returns the #NUM! error value.

MIN, MEDIAN, and MAX return the same value as QUARTILE.EXC when quart is equal to 0 (zero), 2, and 4, respectively.
QUARTILE.INC
Returns the specified quartile of a set of supplied numbers, based on percentile value 0  1 (inclusive)
Syntax:
QUARTILE.INC(array,quart)
Where:

array denotes the array or cell range of numeric values for which you want the quartile value.

quart indicates which value to return.
If quart equals  QUARTILE.INC returns 

0  Minimum value. 
1  First (25th percentile) 
2  Median value (50th percentile) 
3  Third quartile (75th percentile) 
4  Maximum value 
Remarks:

If array is empty, QUARTILE.INC returns the #NUM! error value.

If quart is not an integer, it is truncated.

If quart < 0 or if quart > 4, QUARTILE.INC returns the #NUM! error value.

MIN, MEDIAN, and MAX return the same value as QUARTILE.INC when quart is equal to 0 (zero), 2, and 4, respectively.
RANK.AVG
Returns the statistical rank of a given value, within a supplied array of values (if more than one value has same rank, the average rank is returned)
Syntax:
RANK.AVG(number,ref,[order])
Where:

Number denotes the number whose rank you want to find.

Ref denotes an array of, or a reference to, a list of numbers. Nonnumeric values in Ref are ignored.

Order is a number specifying how to rank number.
Remarks:

If Order is 0 (zero) or omitted, Excel ranks number as if ref were a list sorted in descending order.

If Order is any nonzero value, Excel ranks number as if ref were a list sorted in
RANK.EQ
The Rank.Eq
function returns the statistical rank of a given value within a supplied array of values.
Syntax:
RANK.EQ(number, ref)
where:

number is the value for which you want to find the rank.

ref is an array of values containing the supplied number.
RSQ
The RSQ
returns the square of the Pearson product moment correlation coefficient through data points in known_y’s and known_x’s.
Syntax:
RSQ(known_y’s, known_x’s)
where:

known_y’s is an array or range of data points.

known_x’s is an array or range of data points.
SKEW
Returns the skewness of a distribution
Syntax:
SKEW(number1, [number2], …)
Where:
number1, number2, … Number1 is required, subsequent numbers are optional. 1 to 255 arguments for which you want to calculate skewness. You can also use a single array or a reference to an array instead of arguments separated by commas.
SKEW.P
Returns the skewness of a distribution
Syntax:
SKEW.P(number 1, [number 2],…)
Where:
number 1, number 2,… Number 1 is required, subsequent numbers are optional. Number 1, number 2,… are 1 to 254 numbers or names, arrays, or reference that contain numbers for which you want the population skewness.
Remarks:

Arguments can either be numbers or names, arrays, or references that contain numbers.

Logical values and text representations of numbers that you type directly into the list of arguments are counted.

If an array or reference argument contains text, logical values, or empty cells, those values are ignored; however, cells with the value zero (0) are included.

SKEW.P uses the standard deviation of an entire population, not a sample.

If arguments are values that are not valid, SKEW.P returns the #NUM! error value.

If arguments use data types that are not valid, SKEW.P returns the #VALUE! error value.

If there are fewer than three data points, or the sample standard deviation is zero, SKEW.P returns the #DIV/0! Error value.
SLOPE
Returns the slope of the linear regression line through a supplied series of x and y values
Syntax:
SLOPE(known_y’s, known_x’s)
Where:

known_y’s denotes an array or cell range of numeric dependent data points.

known_x’s denotes the set of independent data points.
SMALL
The Small
returns the kth smallest value in a data set.
Syntax:
SMALL(array, k)
where:

array is an array or range of numerical data for which you want to determine the kth smallest value.

k is the position (from the smallest) in the array or range of data to return.
STANDARDIZE
The Standardize
returns a normalized value from a distribution characterized by mean and standard_dev.
Syntax:
_Standardize(x, mean, standard_dev))
where:

x is the value that you want to normalize.

mean is the arithmetic mean of the distribution.

standard_dev is the standard deviation of the distribution.
Remarks:
 standard_dev must be > 0.
STDEV
Returns the standard deviation of a supplied set of values (which represent a sample of a population).
Syntax:
STDEV(number1,[number2],…)
where:

number1 is the first number argument corresponding to a sample of a population.

number2… is the number arguments 2 to 255 corresponding to a sample of a population. You can also use a single array or a reference to an array instead of arguments separated by commas.
STDEVA
Estimates standard deviation based on a sample. The standard deviation is a measure of how widely values are dispersed from the average value (the mean). Text and logical values such as True and False are also included in the calculation.
Syntax:
STDEVA(value1, value2 , …)
where:
 value1, value2, … are values corresponding to a sample of a population. You can also use a single array or a reference to an array instead of arguments separated by commas.
Remarks:
 Arguments that contain True evaluate as 1; arguments that contain text or False evaluate as 0 (zero).
STDEVPA
Calculates the standard deviation based on the entire population given as arguments, including text and logical values.
Syntax:
STDEVPA(value1, value2, …)
where:
 value1, value2, … are values corresponding to a population. You can also use a single array or a reference to an array instead of arguments separated by commas.
Remarks:
 Arguments that contain True evaluate as 1; arguments that contain text or False evaluate as 0 (zero).
STDEV.P
The STDEV.P
function calculates the standard deviation of a supplied set of values.
Syntax:
STDEV.P(number1,[number2],…])
where:

number1 is the first number argument corresponding to a population.

number2 … are the arguments 2 to 254 corresponding to a population.
Remarks:

Arguments can either be numbers or names, arrays, or references that contain numbers.

The standard deviation is calculated by using the n method.

Arguments that are error values or text that cannot be translated into numbers cause errors.
STDEV.S
The STDEV.S
function calculates the sample standard deviation of a supplied set of values.
Syntax:
STDEV.S(number1,[number2],…])
where:

number1 is the first number argument corresponding to a population.

Number2, … are the arguments 2 to 254 corresponding to a population.
Remarks:

Arguments can either be numbers or names, arrays, or references that contain numbers.

The standard deviation is calculated by using the n method.

Arguments that are error values or text that cannot be translated into numbers cause errors.
STEYX
Returns the standard error of the predicted yvalue for each x in the regression line for a set of supplied x and y values
Syntax:
STEYX(known_y’s, known_x’s)
Where:

Known_y’s denotes an array or range of dependent data points.

Known_x’s denotes an array or range of independent data points
T.DIST
The T.Dist
returns the Percentage Points (probability) for the Student tdistribution where a numeric value (x) is a calculated value of t for which the Percentage Points are to be computed.
Syntax:
TDIST(x,deg_freedom,tails)
where:

X is the numeric value at which to evaluate the distribution.

Deg_freedom is an integer indicating the number of degrees of freedom.

Tails is the number of distribution tails to return. If Tails = 1, TDIST returns the onetailed distribution. If Tails = 2, TDIST returns the twotailed distribution.
Remarks:

If any argument is nonnumeric, TDIST returns the
#VALUE!
error value. 
If Deg_freedom < 1, TDIST returns the #NUM! error value.

The Deg_freedom and Tails arguments are truncated to integers.

If Tails is any value other than 1 or 2, TDIST returns the #NUM! error value.

If x < 0, then TDIST returns the #NUM! error value.

If Tails = 1, TDIST is calculated as TDIST = P( X>x ), where X is a random variable that follows the tdistribution. If Tails = 2, TDIST is calculated as TDIST = P(X > x) = P(X > x or X < x).

Since x < 0 is not allowed, to use TDIST when x < 0, note that TDIST(x,df,1) = 1 – TDIST(x,df,1) = P(X >x) and TDIST(x,df,2) = TDIST(x,df,2) = P(X > x).
T.INV
The T.INV
returns the lefttailed inverse of the Student’s tdistribution.
Syntax:
T.INV(probability,deg_freedom)
where:

Probability is the probability associated with the Student’s tdistribution.

Deg_freedom is the number of degrees of freedom with which to characterize the distribution.
Remarks:

If either argument is nonnumeric, T.INV returns the
#VALUE!
error value. 
If probability <= 0 or if probability >1, T.INV returns the #NUM! error value.

If deg_freedom is not an integer, it is truncated.

If deg_freedom < 1, T.INV returns the #NUM! error value.
TRIMMEAN
Returns the mean of the interior of a data set. TRIMMEAN
calculates the mean taken by excluding a percentage of data points from the top and bottom tails of a data set.
Syntax:
TRIMMEAN(array, percent)
where:

array is the array or range of values to trim and average.

percent is the fractional number of data points to exclude from the calculation. For example, if percent = 0.2, 4 points are trimmed from a data set of 20 points (20 x 0.2): 2 from the top and 2 from the bottom of the set.
Remarks:

Percent must be >= 0 and <= 1.

TRIMMEAN rounds off the number of excluded data points down to the nearest multiple of 2. If percent = 0.1, 10 percent of 30 data points equals 3 points. For symmetry, TRIMMEAN excludes a single value from the top and bottom of the data set.
VAR
Returns the variance of a supplied set of values (which represent a sample of a population)
Syntax:
VAR(number1,[number2],…)
Where:

Number1 denotes the first number argument corresponding to a sample of a population.

Number2, … denotes number arguments 2 to 255 corresponding to a sample of a population.
VAR.P
Calculates variance based on the entire population (ignores logical values and text in the population).
Syntax:
VAR.P(number1,[number2],…)
where:

number1 is the first number argument corresponding to a population.

number2, … is Optional. Number arguments 2 to 254 corresponding to a population.
Remarks:

VAR.P assumes that its arguments are the entire population. If your data represents a sample of the population, then compute the variance by using VAR.S.

Arguments can either be numbers or names, arrays, or references that contain numbers.

Logical values, and text representations of numbers that you type directly into the list of arguments are counted.

If an argument is an array or reference, only numbers in that array or reference are counted. Empty cells, logical values, text, or error values in the array or reference are ignored.

Arguments that are error values or text that cannot be translated into numbers cause errors.

If you want to include logical values and text representations of numbers in a reference as part of the calculation, use the VARPA function.
VARPA
Calculates variance based on the entire population. In addition to numbers and text, logical values such as True and False are also included in the calculation.
Syntax:
VARPA(value1, value2, …)
where:
 value1, value2, … are arguments corresponding to a population.
Remarks:

VARPA assumes that its arguments are the entire population. If your data represents a sample of the population, you must compute the variance using VARA.

Arguments that contain True evaluate as 1; arguments that contain text or False evaluate as 0 (zero). If the calculation does not include text or logical values, use the VARP worksheet function instead.
VARA
The VarA
function returns the variance of a population based on a sample of numbers, text, and logical values (example: TRUE or FALSE).
Syntax:
VARA( value1, value2, … value_n )
where:
 value1, value2, … value_n are the sample values. They can be numbers, text, and logical values. Values that are TRUE are evaluated as 1. Values that are FALSE or text values are evaluated as 0. 30 values can be entered.
WEIBULL
Returns the Weibull distribution
Syntax:
WEIBULL(x,alpha,beta,cumulative)
Where:

x denotes the value at which to evaluate the function.

alpha denotes a parameter to the distribution.Beta denotes a parameter to the distribution.

cumulative determines the form of the function.
WEIBULL.DIST
The Weibull.Dist
function returns the Weibull Distribution.
Syntax:
WEIBULL.DIST(x,alpha,beta,cumulative)
where:

x is the value that evaluates the function.

alpha is a parameter of the distribution.

beta is a parameter of the distribution.

cumulative determines the form of the function.
Remarks:

#NUM!
occurs when x is lesser than zero and when alpha or beta is equal to or lesser than zero. 
#VALUE!
occurs when beta is nonnumeric.
ZTEST
ZTest
function returns the onetailed probability value of a ztest.
Syntax:
ZTEST(array,T_value,sigma)
where:

array is an array or range of data.

T_value is the value to test..

sigma is the population (known) standard deviation.
CHITEST
CHITEST
function returns the value from the chisquared (χ2) distribution.
Syntax:
CHITEST(actual_range,expected_range)
where:

Actual_range : The range of data to test against expected values.

Expected_range :The range of data that contains the ratio of the product of row and column totals to the grand total.
FDIST
FDIST
function returns the (righttailed) F probability distribution (degree of diversity) which measures the degree of diversity for two data sets.
Syntax:
FDIST(x,deg_freedom1,deg_freedom2)
where:

X : The numeric value at which to evaluate the function.

Deg_freedom1 : The integer specifying the numerator degrees of freedom.

Deg_freedom2 :The integer specifying the denominator degrees of freedom.
Remarks:

The argument is nonnumeric, it returns the
#VALUE!
error message. 
The argument (x) is negative, it returns the
#NUM!
error message. 
The argument (deg_freedom1 or deg_freedom2) is not an integer, it is truncated.

The argument (deg_freedom1 or deg_freedom2) is less than 1 or greater than equal to 10^10, it returns the
#NUM!
error message.
FINV
FINV
function returns the inverse of the (righttailed) F probability distribution for a given probability.
Syntax:
FINV(probability,deg_freedom1,deg_freedom2)
where:

Probability : A probability to evaluate the inverse F cumulative distribution.

Deg_freedom1 : The integer specifying the numerator degrees of freedom.

Deg_freedom2 :The integer specifying the denominator degrees of freedom.
Remarks:

The argument is nonnumeric, it returns the
#VALUE!
error message. 
The argument(probability) < 0 or probability > 1, it returns the
#NUM!
error message. 
The arguments(deg_freedom1 or deg_freedom2) is not an integer, it is truncated.

The arguments(deg_freedom1 or deg_freedom2) less than 1 or greater than equal to 10^10, it returns the
#NUM!
error message.
FISHER
FISHER
function returns the Fisher transformation of the given value. This transformation produces a function that is normally distributed rather than skewed. Use this function to perform hypothesis testing on the correlation coefficient.
Syntax:
FISHER(x)
where:
 X : A numeric value for which you want calculate the Fisher Transformation.
Remarks:

The argument (x) is nonnumeric, it returns the
#VALUE!
error message. 
The argument (x) ≤ 1 or if x ≥ 1, it returns the
#NUM!
error message.
FISHERINV
FISHERINV
function returns the inverse of the Fisher transformation of the given value. Use this transformation when analyzing correlations between ranges or arrays of data.
Syntax:
FISHERINV(y)
where:
 Y : The numeric value for which you want to calculate the inverse of the Fisher transformation.
Remarks:
 The argument (y) is nonnumeric, it returns the
#VALUE!
error message.
RANK
RANK
function returns the rank of a number when compared to a list of other numbers. The rank of a number is its size relative to other values in a list.
Syntax:
RANK(number,ref,[order])
where:

Number : The is the number value whose rank you want to find.

Ref : It can be a array of, or a reference to, a list of numbers. Nonnumeric values in ref are ignored.

Order :This is a number that specifies how the ranking will be done.
Z.TEST
Z.TEST
function calculates the onetailed Pvalue of a ztest.
Syntax:
Z.TEST(array,x,[sigma])
where:

Array : The array or range of data against which the hypothesized sample mean is to be tested.

x : The hypothesized sample mean.

Sigma :This represents the population (known) standard deviation. If omitted, the function used the sample standard deviation.
BETA.DIST
BETA.DIST
function calculates the cumulative beta distribution function or the probability density function of the Beta distribution, for a given set of parameters.
Syntax:
BETA.DIST(x,alpha,beta,cumulative,[A],[B])
where:

X : The value between A and B at which to evaluate the function

Alpha : A parameter of the distribution.

Beta : A parameter of the distribution.

Cumulative :A logical value that determines the form of the function. If cumulative is
TRUE
, it returns the cumulative distribution function. ifFALSE
, it returns the probability density function. 
A (Optional):It is a lower bound to the interval of x.

B (Optional): It is a upper bound to the interval of x.
Remarks:

The argument is nonnumeric, it returns the
#VALUE!
error value. 
The argument (alpha) ≤ 0 or beta ≤ 0,it returns the
#NUM!
error value. 
The argument (x) < A, x > B, or A = B, it returns the
#NUM!
error value. 
If you omit values for the arguments (A and B), it uses the standard cumulative beta distribution, so that A = 0 and B = 1.
LINEST
LINEST
function uses the least squares method to calculate the statistics for a straight line and returns an array describing that line.
Syntax:
LINEST(known_y’s, [known_x’s], [const], [stats]))
where:

known_y’s : This is the set of yvalues from the line equation.

known_x’s (Optional). This is a a set of xvalues from the line equation.

const (Optional). This is a logical value specifying whether to force the constant b to equal 0.

If const is
TRUE
or omitted, b is calculated normally. 
If const is
FALSE
, b is set equal to 0 
stats (Optional). This is a logical value specifying whether to return additional regression statistics.