Excel Functions

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Type Function Description
numeric COMBIN( number, number_chosen )

$C(n,r) = \frac{n!}{r!(n-r)!}$

calculates the number of combinations (in any order) of a given number objects from a set
numeric COMBINA( number, number_chosen )

$C(n,r) = \frac{(n+r-1)!}{r!(n-1)!}$

calculates the number of combinations, with repetitions, of a given number objects from a set
numeric EXP( number )

$e^{ln(x)} = x$

calculates the value of the mathematical constant e, raised to the power of number
numeric FACT( number )

$n! = (n)(n-1)(n-2)...(1)$

returns the factorial of a supplied number
numeric FACTDOUBLE( number )

if n is even $n! = (n)(n-2)(n-4)...(2)$

if n is odd $n! = (n)(n-2)(n-4)...(1)$

returns the double factorial of a number, using only odd numbers if number is odd, and only even numbers if number is even
numeric INTERCEPT( known_y's, known_x's )

$b = \bar y - m \bar x$

calculates the intercept (the value at the intersection of the y axis) of the linear regression line through a supplied set of x- and y- values
numeric LARGE(range, n) returns the nth largest number in the range
numeric LINEST( known_y's, [known_x's], [const], [stats] ) returns statistical information on the line of best fit, through a supplied set of x- and y- values; the basic statistical information returned is the array of constants, mn, mn-1, ... , b for the equation

$y = m_{1}x_{1} + m_{2} x_{2} + ... + b$

numeric LN( number )

$ln(a)^x = xln(a)$

$ln(e^x) = x$

calculates the natural logarithm of number
numeric LOG( number, [base] )

$log_a(a^x) = xlog_a(a) = x$

$log_a(xy) = log_a(x) + log_a(y)$

$log_a\left(\frac{x}{y}\right) = log_a(x) - log_a(y)$

$log_a(x) = \frac{log_b(x)}{log_b(a)}$

calculates the logarithm of a given number, to a supplied base; if base is omitted the base is assumed to be 10
numeric MAX( number1, [number2], ...) returns the largest value from a supplied set or range of numeric values
numeric MAXA( number1, [number2], ... ) returns the largest value from a supplied set of numeric values, while counting text and the logical value FALSE as the value 0 and counting the logical value TRUE as the value 1
numeric MAXIFS( max_range, criteria_range1, criteria1, [criteria_range2, criteria2], ... ) returns the maximum value from a subset of values that are specified according to one or more criteria
numeric MIN( number1, [number2], ...) returns the smallest value from a supplied set or range of numeric values
numeric MINA( number1, [number2],... ) returns the smallest value from a supplied set of numeric values, while counting text and the logical value FALSE as the value 0 and counting the logical value TRUE as the value 1
numeric MINIFS( min_range, criteria_range1, criteria1, [criteria_range2, criteria2],... ) returns the minimum value from a subset of values that are specified according to one or more criteria
numeric PERMUT( number, number_chosen )

$P(n,r) = \frac{n!}{(n-r)!}$

calculates the number of permutations, without repetition, of a specified number of objects from a set of objects
numeric PERMUTATIONA( number, number_chosen )

$n^r$

calculates the number of permutations, with repetitions, of a specified number of objects from a set
numeric RAND() returns a random number between 0 and 1
numeric RANDBETWEEN( bottom, top ) generates a random integer between two supplied integers
numeric SLOPE( known_y's, known_x's )

$m = \frac {\sum (x- \bar x)(y - \bar y)}{\sum (x - \bar x)^2}$

calculates the slope of the linear regression line through a supplied set of x- and y- values
numeric SMALL(range, n) returns the nth smallest number in the range
rounding CEILING( number, significance ) rounds a supplied number away from zero, to the nearest multiple of a given number
rounding CEILING.MATH( number, [significance], [mode] ) rounds a supplied number up to a supplied multiple of significance
rounding CEILING.PRECISE( number, [significance] ) rounds a supplied number up, regardless of the number's sign, to the nearest multiple of a given number
rounding EVEN( number ) rounds a supplied number away from zero (i.e. rounds a positive number up and a negative number down), to the next even number
rounding FLOOR( number, significance ) rounds a supplied number to towards zero to the nearest multiple of a specified significance
rounding FLOOR.MATH( number, [significance], [mode] ) rounds a supplied number down to a supplied multiple of significance
rounding FLOOR.PRECISE( number, [significance] ) rounded towards zero (becoming less positive) and negative numbers are rounded away from zero (becoming more negative)
rounding INT( number ) truncates a supplied number down to the closest integer
rounding ISO.CEILING( number, [significance] ) rounds a supplied number up regardless of the number's sign, to the nearest multiple of a supplied significance
rounding MROUND( number, multiple ) rounds a supplied number up or down to the nearest multiple of a given number
rounding ODD( number ) rounds a supplied number away from zero (i.e. rounds a positive number up and a negative number down), to the next odd number
rounding ROUND( number, num_digits ) rounds a supplied number up or down, to a specified number of decimal places
rounding ROUNDDOWN( number, num_digits ) rounds a supplied number down towards zero, to a specified number of decimal places
rounding ROUNDUP( number, num_digits ) rounds a supplied number up, away from zero, to a specified number of decimal places
rounding TRUNC( number, [num_digits] ) truncates a supplied number to a specified number of decimal places
number-to-text BAHTTEXT( number ) converts a number into Thai text, with the suffix "Baht"
number-to-text BASE( number, radix, [min_length] ) converts a number into a supplied base (radix), and returns a text representation of the calculated value
number-to-text CHAR( number ) returns the character relating to a supplied character set number (from 1 to 255)
number-to-text DOLLAR( number, [decimals] ) rounds a supplied number to a specified number of decimal places and then converts this into a text string with a currency format
number-to-text FIXED( number, [decimals], [no_commas] ) rounds a number to a specified number of decimal places and converts it to text
number-to-text TEXT( value, format_text ) converts a supplied numeric value into text, in a user-specified format
number-to-text UNICHAR( number ) returns the Unicode character relating to a supplied number
text-to-number CODE( text ) converts the first character of a supplied text string into the associated numeric character set code used by the local computer
text-to-number DECIMAL( text, radix ) converts a text representation of a number in a specified base, into a decimal value
text-to-number NUMBERVALUE( text, [decimal_separator], [group_separator] ) converts a text string into a number
text-to-number UNICODE( text ) returns the code point for the first character of a supplied text string
text-to-number VALUE( text ) converts a text string that contains digits, numbers with commas, numbers written in scientific notation into a decimal number
text ARABIC( text ) converts a Roman numeral into an Arabic numeral
text CLEAN( text ) cleans non-printable characters from the text in a cell
text LEFT( text, [num_chars] ) returns a specified number of characters from the start of a supplied text string
text LEN( text ) returns the length of a text string
text LOWER( text ) converts all characters in a supplied text string to lower case
text MID( text, start_num, num_chars ) returns a specified number of characters from the middle of a supplied text string
text PROPER( text ) converts all characters in a text string to proper case, i.e., letters that do not follow another letter are upper case and all other characters are lower case
text REPLACE( old_text, start_num, num_chars, new_text ) replaces all or part of a text string with another string
text RIGHT( text, [num_chars] ) returns a specified number of characters from the end of a supplied text string
text SUBSTITUTE( text, old_text, new_text, [instance_num] ) replaces one or more instances of a given text string, within an original text string
text SWITCH( expression, value1, result1,
[value2, result2], [value3, result3], ..., [default] )
compares a number of supplied values to a supplied test expression and returns a result corresponding to the first value that matches the test expression
text T( value ) tests if a supplied value is text
text TEXTJOIN( [delimiter], [ignore_empty], text1, [text2], ... ) joins together a series of supplied text strings into one combined text string
text TRIM( text ) removes extra spaces, except for single spaces between words or characters, from a supplied text string
text UPPER( text ) converts all characters in a supplied text string to upper case
miscellaneous TYPE( value ) returns an integer that represents the value's data type
database CHOOSE( index_num, value1, [value2], ... ) returns a value from an array, that corresponds to a supplied index number (position)
database DAVERAGE( database, field, criteria ) calculates the average (statistical mean) of values in a field (column) in a database for selected records, that satisfy user-specified criteria
database DCOUNT( database, [field], criteria ) returns the number of cells containing numeric values, in a field (column) of a database for selected records only; the records to be included in the count are those that satisfy a set of one or more user-specified criteria
database DCOUNTA( database, [field], criteria ) function returns the number of non-blank cells, in a field (column) of a database for selected records only; the records to be included in the count are those that satisfy a set of one or more user-specified criteria
database DGET( database, field, criteria ) returns a single value from a column of a database; the record is selected via a set of one or more user-specified criteria
database DMAX( database, field, criteria ) finds the maximum value in a field (column) in a database for selected records only; the records to be included in the calculation are defined by a set of one or more user-specified criteria
database DMIN( database, field, criteria ) finds the minimum value in a field (column) in a database for selected records only; the records to be included in the calculation are defined by a set of one or more user-specified criteria
database DPRODUCT( database, field, criteria ) calculates the product of a field (column) in a database for selected records, that satisfy user-specified criteria
database DSTDEV( database, field, criteria )

sample standard deviation = $\sqrt \frac { \sum { \left( x - \bar{x} \right) }^2}{n-1}$

calculates the sample standard deviation of a field (column) in a database for selected records only; the records to be included in the calculation are defined by a set of one or more user-specified criteria
database DSTDEVP( database, field, criteria ) calculates the standard deviation of a field (column) in a database for selected records only; the records to be included in the calculation are defined by a set of one or more user-specified criteria
database DSUM( database, field, criteria )

sum = $\sum{x}$

calculates the sum of a field (column) in a database for selected records, that satisfy user-specified criteria
database DVAR( database, field, criteria )

sample variance = $s^2 = \frac { \sum { \left( x - \bar{x} \right) }^2}{n-1}$

calculates the sample variance of a field (column) in a database for selected records only; the records to be included in the calculation are defined by a set of one or more user-specified criteria
database DVARP( database, field, criteria )

variance = $\sigma^2 = \frac {\sum { \left( {x - \mu } \right) }^2}{n}$

calculates the variance (for an entire population), of the values in a field (column) in a database for selected records only; the records to be included in the calculation are defined by a set of one or more user-specified criteria
database GETPIVOTDATA( data_field, pivot_table, [field1], [item1], [field2], [item2], ...) extracts data from specified fields of a pivot table
database HLOOKUP( lookup_value, table_array, row_index_num, [range_lookup] ) looks up a given value in the top row of a data array or table, and returns the corresponding value from another row of the array
database LOOKUP( lookup_value, lookup_vector, [result_vector] ) looks up a value in a data vector (a 1-dimensional list of data) and returns the corresponding value from a second data vector
database LOOKUP( lookup_value, array) looks up a value in the first column or row of a supplied data array (i.e. a 2-dimensional table of data) and returns the corresponding value from the last column or row of the array
database MATCH( lookup_value, lookup_array, [match_type] ) looks up a value in an array, and returns the position of the value within the array
database VLOOKUP( lookup_value, table_array, row_index_num, [range_lookup] ) looks up a given value in the left-hand column of a data array or table, and returns the corresponding value from another column of the array
statistics AVEDEV( number1, [number2], ... )

average deviation = $\frac {\sum |x - \bar x|}{n}$

calculates the average deviation of a supplied set of values
statistics AVERAGE(range)

mean $\bar x = \frac {\sum x}{n}$

calculate the mean of the range
statistics AVERAGEA( value1, [value2], ... )

mean $\bar x = \frac {\sum x}{n}$

arithmetic mean of a list of supplied numbers
statistics AVERAGEIF(range, criterion)

mean $\bar x = \frac {\sum x}{n}$

calculate the average of the range based on a criterion
statistics AVERAGEIFS( average_range, criteria_range1, criteria1, [criteria_range2, criteria2], ... )

mean $\bar x = \frac {\sum x}{n}$

finds entries in one or more arrays, that satisfy a set of supplied criteria, and returns the average
statistics CONFIDENCE.NORM(alpha, std_dev, size) returns the confidence interval for a population mean, using a normal distribution
statistics CONFIDENCE.T(alpha, std_dev, size) returns the confidence interval for a population mean, using a Student's t distribution
statistics COUNT( value1, [value2], ... ) returns the count of numeric values in a supplied set of cells or values including both numbers and dates
statistics COUNTA( value1, [value2], ... ) returns the number of non-blanks within a supplied set of cells or values
statistics COUNTBLANK( range ) returns the number of blank cells in a supplied range
statistics COUNTIF( range, criteria ) returns the number of cells within a supplied range, that satisfy a given criteria
statistics COUNTIFS( criteria_range1, criteria1, [criteria_range2, criteria2], ... ) returns the number of rows within a table, that satisfy a set of given criteria
statistics DEVSQ( number1, [number2], ... )

DEVSQ = $\sum {(x^2 - y^2)}$

calculates the sum of the squared deviations from the sample mean
statistics FREQUENCY( data_array, bins_array ) returns the number of values that fall into specified ranges
statistics GEOMEAN( number1, [number2], ... ) calculates the geometric mean of a supplied set of values where the number arguments are one or more positive numeric values or arrays of numeric values
statistics GROWTH( known_y's, [known_x's], [new_x's], [const] ) calculates the exponential growth curve through a given set of y-values and (optionally), one or more sets of x-values; the function then extends the curve to calculate additional y-values for a further supplied set of new x-values
statistics HARMEAN( number1, [number2], ... )

$H_x = \frac {n}{\sum \frac{1}{x}}$

calculates the harmonic mean of a supplied set of values
statistics LOGEST( known_y's, [known_x's], [const], [stats] ) returns statistical information on the exponential curve of best fit, through a supplied set of x- and y- values; the basic statistical information returned is the array of constants,
mn, mn-1, ... , b (or the constants m and b if there is a single range of x-values), for the exponential curve equation; additional regression statistics be returned
statistics MEDIAN( range ) calculates the median of a supplied set of values
statistics MODE.MULT( range ) returns a vertical array of the most frequently occurring values
statistics MODE.SNGL( range ) returns the statistical mode (the most frequently occurring value) within a list of supplied numbers
statistics PERCENTILE.EXC( array, k ) returns the k'th percentile (i.e. the value below which k% of the data values fall) for a supplied range of values and a supplied k (between 0 & 1 exclusive)
statistics PERCENTILE.INC( array, k ) returns the k'th percentile (i.e. the value below which k% of the data values fall) for a supplied range of values and a supplied k
statistics PERCENTRANK.EXC( array, x, [significance] ) calculates the relative position, between 0 and 1 (exclusive), of a specified value within a supplied array
statistics PERCENTRANK.INC( array, x, [significance] ) calculates the relative position, between 0 and 1 (inclusive), of a specified value within a supplied array
statistics QUARTILE.EXC( array, quart ) returns a requested quartile of a supplied range of values, based on a percentile range of 0 to 1 exclusive
statistics QUARTILE.INC( array, quart ) returns a requested quartile of a supplied range of values, based on a percentile range of 0 to 1 (inclusive)
statistics RANK.AVG( number, ref, [order] ) returns the statistical rank of a given value, within a supplied array of values; if there are duplicate values in the list, the average rank is returned
statistics RANK.EQ( number, ref, [order] ) returns the statistical rank of a given value, within a supplied array of values; if there are duplicate values in the list, these are given the same rank
statistics STANDARDIZE(x, mean, standard_dev) returns the z value for a specified value, mean, and standard deviation
statistics STDEVA( number1, [number2], ... )

sample standard deviation = $\sqrt \frac { \sum { \left( x - \bar{x} \right) }^2}{n-1}$

calculates the sample standard deviation of a supplied set of values; logical values can be included
statistics STDEV.P(range)

standard deviation = $\sqrt \frac { \sum { \left( x - \bar{x} \right) }^2}{n}$

statistics STDEVPA( number1, [number2], ... )

standard deviation = $\sqrt \frac { \sum { \left( x - \bar{x} \right) }^2}{n}$

calculates the standard deviation of a population; logical values can be included, assumes an entire population
statistics STDEV.S(range)

sample standard deviation = $\sqrt \frac {\sum { \left( x - \bar{x} \right) }^2}{n-1}$

calculates the standard deviation of a sample
statistics STEYX( known_y's, known_x's ) calculates the standard error for the line of best fit, through a supplied set of x- and y- values
statistics SUMPRODUCT( range1,range2, ... ) calculates the sum of the product of the ranges
statistics SUMSQ( range1, range2, ... ) sum of the squares of the values in the given range(s)
statistics SUMX2PY2( array_x, array_y )

SUMX2PY2 = $\sum {(x^2 + y^2)}$

calculates the sum of the sum of the squares of x and y
statistics SUMX2MY2( array_x, array_y )

SUMX2MY2 = $\sum {(x^2 - y^2)}$

calculates the sum of the difference of the squares of x and y
statistics SUMXMY2( array_x, array_y )

SUMXMY2 = $\sum {(x-y)^2}$

calculates the sum of the squares of the differences of x and y
statistics TREND( known_y's, [known_x's], [new_x's], [const] ) calculates the linear trend line through a given set of y-values and (optionally), a given set of x-values
statistics TRIMMEAN(array, percent ) calculates the trimmed mean, or truncated mean, of a supplied set of values by truncating percent/2 values from each end of the array
statistics VARA(number1, [number2], ... )

sample variance = $s^2 = \frac { \sum { \left( x - \bar{x} \right) }^2}{n-1}$

calculates the sample variance of a supplied set of values; logical values may be counted
statistics VAR.P( number1, [number2], ... )

variance = $\sigma^2 = \frac {\sum{(x - \mu )}^2}{n}$

returns the variance of a given set of values
statistics VAR.S( number1, [number2], ... )

sample variance = $s^2 = \frac {\sum{\left(x - \bar{x}\right)}^2}{n-1}$

calculates the sample variance of a supplied set of values
probability BETA.DIST( x, alpha, beta, cumulative, [A], [B] ) calculates the cumulative beta distribution function or the probability density function of the Beta distribution, for a supplied set of parameters
probability BETA.INV(probability, alpha, beta, [A], [B] ) calculates the inverse of the cumulative beta probability density function for a supplied probability
probability BINOM.DIST(number_s, trials, probability_s, cumulative )

$binom(n,p,k) = \left ( {\begin{matrix} n \\ p \end{matrix}} \right ) p^k (1-p)^{n-k} = \frac {n!}{k!(n-k)!} p^k (1-p)^{n-k}$

returns the binomial distribution probability for a given number of successes from a specified number of trials
probability BINOM.DIST.RANGE(trials, probability_s, number_s, [number_s2] ) returns the binomial distribution probability for the number of successes from a specified number of trials falling into a specified range
probability BINOM.INV( trials, probability_s, alpha ) returns the inverse of the cumulative binomial distribution
probability CHISQ.DIST( x, degrees_freedom, cumulative )

$\chi^{2} = \sum_{i=1}^r \sum_{i=1}^c \frac {\left ( O_{ij} - E_{ij} \right )^{2}}{E_{ij}}$

calculates the probability density function or the cumulative distribution function for the chi-square distribution
probability CHISQ.DIST.RT( x, degrees_freedom ) calculates the right-tailed probability of the chi-square distribution
probability CHISQ.INV( probability, degrees_freedom ) calculates the inverse of the left-tailed probability of the chi-square distribution
probability CHISQ.INV.RT(probability, degrees_freedom ) calculates the inverse of the right-tailed probability of the chi-square distribution
probability CHISQ.TEST(actual_range, expected_range ) performs the chi-square test on two supplied data sets of observed and expected frequencies, and returns the probability that the differences between the sets are simply due to sampling error
probability CORREL( array1, array2 )

$r = \frac {\sum (x-\bar x)(y-\bar y)}{\sqrt {{\sum (x-\bar x)^2} {\sum (y-\bar y)^2}}}$

calculates the Pearson Product-Moment Correlation Coefficient for two sets of values
probability EXPON.DIST( x, lambda, cumulative )

probability density function $f(x, \lambda) = \lambda e^{-\lambda x}$
cumulative exponential distribution $F(x, \lambda) = 1 - e^{-\lambda x}$

probability F.DIST( x, deg_freedom1, deg_freedom2,
cumulative )
calculates the probability density function or the cumulative distribution function for the F-distribution
probability F.DIST.RT( x, deg_freedom1, deg_freedom2 ) calculates the right-tailed F probability distribution, which measures the degree of diversity between two data sets
probability FISHER( x ) calculates the Fisher transformation for a supplied value
probability FISHERINV( y ) calculates the inverse of the Fisher transformation and returns a value between -1 and +1
probability F.TEST( array1, array2) returns the F-test for two supplied arrays
probability GAMMA(number)

$\Gamma(n) = \int_0^\infty x^{n-1} e^{-x} dx $

returns the value of the Gamma Function, Γ(n), for a specified number, n
probability GAMMA.DIST( x, alpha, beta, cumulative) calculates the value of either the cumulative distribution or the probability density function for the gamma distribution
probability GAMMA.INV( probability, alpha, beta) returns the inverse of the gamma cumulative distribution
probability GAMMALN.PRECISE( x ) returns the natural logarithm of the gamma function, Γ(n)
probability GAUSS( z ) returns the probability that a member of a standard normal population will fall between the mean and a specified number of standard deviations from the mean
probability HYPGEOM.DIST( sample_s, number_sample, population_s, number_pop, cumulative )

$h(x, n, M, N) = \frac {\begin {pmatrix} M \\ x \\ \end {pmatrix} \begin {pmatrix} N - M \\ n - x \\ \end {pmatrix} }{\begin {pmatrix} N \\ n \\ \end {pmatrix} }$

returns the value of the hypergeometric distribution for a given number of successes from a sample of a population
probability KURT( number1, [number2], ... ) calculates the kurtosis of a supplied set of values
probability LOGNORM.DIST( x, mean, standard_dev, cumulative )

$LOGNORM.DIST(x,\mu,\sigma) = NORM.S.DIST \left ( \frac { ln(x) - \mu}{\sigma } \right )$

calculates the log-normal probability density function or the cumulative log-normal distribution function for a supplied value of x
probability LOGNORM.INV( probability, mean, standard_dev ) calculates the inverse of the cumulative log-normal distribution function of x, for a supplied probability
probability NEGBINOM.DIST(number_f, number_s, probability_s, cumulative) calculates the probability mass function or the cumulative distribution function for the negative binomial distribution
probability NORM.DIST( x, mean, standard_dev, cumulative )

$f(x,\mu,\sigma) = \frac {1}{\sigma \sqrt {2 \pi}} e^\frac{-(x-\mu)^2}{2 \sigma^2}$

probability that a number falls at or below a given value of a normal distribution
probability NORMINV( probability, mean, standard_dev) NORM.INV is the inverse of the NORM.DIST function and calculates the x variable given a probability
probability NORM.S.DIST( z, cumulative) translates the number of standard deviations, z, into cumulative probabilities
probability NORM.S.INV( probability ) NORM.S.INV is the inverse of the NORM.S.DIST function; given the probability that a variable is within a certain distance of the mean, it finds the z value
probability PEARSON( array1, array2 )

$r = \frac {\sum (x-\bar x)(y-\bar y)}{\sqrt {{\sum (x-\bar x)^2} {\sum (y-\bar y)^2}}}$

calculates the Pearson product-moment correlation coefficient for two sets of values
probability PHI( x ) returns the value of the density function for a standard normal distribution for a supplied number
probability POISSON.DIST( x, mean, cumulative )

probability density function $f(x, \lambda ) = \frac {e ^{ -\lambda} \lambda^{x}}{x!}$

cumulative Poisson distribution $F(x, \lambda ) = \sum_{k=0}^N \frac {e ^{ -\lambda} \lambda^{x}}{k!}$

calculates the Poisson probability mass function or the cumulative Poisson probability function for a supplied set of parameters
probability PROB( x_range, prob_range, [lower_limit], [upper_limit] ) calculates the probability associated with a given range
probability RSQ( known_y's, known_x's )

$r^2 = \left ( {\frac {\sum (x-\bar x)(y-\bar y)}{\sqrt {{\sum (x-\bar x)^2} {\sum (y-\bar y)^2}}}} \right )^2$

calculates the square of the Pearson product-moment correlation coefficient for two supplied sets of values
probability SKEW( number1, [number2], ... ) calculates the skewness of the distribution of a supplied set of values
probability SKEW.P( number1, [number2], ... ) calculates the skewness of the distribution of a supplied set of values of a population
probability STANDARDIZE( x, mean, standard_dev ) returns a normalized value of a distribution that is characterized by a supplied mean and standard deviation
probability T.DIST( x, degrees_freedom, cumulative ) calculates the one-tailed Student's t-distribution for testing hypotheses on small sample data sets
probability T.DIST.2T( x, degrees_freedom ) calculates the two-tailed Student's t-distribution
probability T.DIST.RT( x, degrees_freedom ) calculates the right-tailed Student's t-distribution
probability T.INV( probability, degrees_freedom ) calculates the left-tailed inverse of the Student's t-distribution
probability T.TEST( array1, array2, tails, type ) calculates the probability associated with the Student's t-test
probability WEIBULL.DIST( x, alpha, beta, cumulative )

probability density function $f(x, \alpha , \beta ) = \frac {\alpha}{\beta ^{\alpha}} x^{\alpha - 1} e^{ - \left ( x/ \beta \right ) ^{\alpha}}$

cumulative Weibull distribution $F(x, \alpha , \beta ) = 1 - e^{ - \left ( x/ \beta \right ) ^{\alpha}}$

calculates the Weibull probability density function or the Weibull cumulative distribution function for a supplied set of parameters
probability Z.TEST( array, x, [sigma] ) calculates the one-tailed probability value of the z-test
trigonometry ACOS( number )

$acos \left ( \frac {adj}{hyp} \right ) = \theta$

returns the arccosine, in radians, in the interval $\left[ {0 , \pi} \right]$
trigonometry ACOSH( number )

$acosh(z) = ln ( z + \sqrt {z - 1} \sqrt { z + 1} )$

calculates the inverse hyperbolic cosine of a number
trigonometry ACOT( number )

$acot \left ( \frac {adj}{opp} \right ) = \theta$

returns the arccotangent of a number, in radians, in the interval $[0 , \pi ]$;
trigonometry ACOTH( number )

$coth(z) = \frac {1}{2} ln \left ( \frac {z + 1}{z - 1} \right )$

calculates the inverse hyperbolic cotangent of a number
trigonometry ASIN( number )

$asin \left ( \frac {opp}{hyp} \right ) = \theta$

returns the arcsine, in radians, in the interval $\left[ {\frac {-\pi}{2} , \frac {\pi}{2}} \right]$
trigonometry ASINH( number )

$asinh(z) = ln ( z + \sqrt { z^2 + 1} )$

calculates the inverse hyperbolic sine of a real number
trigonometry ATAN( number )

$atan \left ( \frac {opp}{adj} \right ) = \theta$

returns the arctangent of a number, in radians, in the interval $\left[ {\frac {-\pi}{2} , \frac {\pi}{2}} \right]$
trigonometry ATAN2( x_num, y_num ) x_num and y_num are the x- and y- coordinates of the point that used to calculate the arctangent, in radians; the returned angle may be positive, representing a counterclockwise angle from the x-axis, or negative, representing a clockwise angle from the x-axis
trigonometry ATANH( number )

$atanh(z) = ln \left ( \frac {\sqrt {1 - z^2 }}{1 - z} \right )$

calculates the inverse hyperbolic tangent of a real number
trigonometry COS( number )

$cos(\theta) = \frac {opp}{adj} = sin \left( \frac {\pi}{2} - \theta \right) = \frac {1}{sec(\theta)}$

calculates the cosine of an angle given in radians
trigonometry COSH( number )

$cosh(x) = \frac {e^x + e^{-x}}{2} = \frac {e^{2x} + 1}{2e^x} = \frac {1 + e^{-2x}}{2e^{-x}} $

returns the hyperbolic cosine of a real number given in radians
trigonometry COT( number )

$cot(\theta) = \frac {adj}{hyp} = \frac {cos(\theta)} {sin(\theta)} = tan \left( \frac {\pi}{2} - \theta \right ) = \frac {1}{tan(\theta)} $

calculates the cotangent of an angle given in radians
trigonometry COTH( number )

$coth(x) = \frac {cosh(x)}{sinh(x)} = \frac {e^x + e^{-x}}{e^x - e^{-x}} = \frac {e^{2x} + 1}{e^{2x} - 1} = \frac {1 + e^{-2x}}{1 - e^{-2x}}$

returns the hyperbolic cotangent of a real number given in radians
trigonometry CSC( number )

$csc(\theta) = \frac {hyp}{opp} = sec \left( \frac {\pi}{2} - \theta \right ) = \frac {1}{sin(\theta)}$

calculates the cosecant of an angle given in radians
trigonometry CSCH( number )

$csch(x) = \frac {1}{sinh(x)} = \frac {2}{e^x - e^{-x}} = \frac {2e^x}{e^{2x} - 1} = \frac {2e^{-x}}{1 -e^{-2x}} $

returns the hyperbolic cosecant of a real number given in radians
trigonometry DEGREES( angle )

degrees = $\frac {\pi}{180^0}$

converts radians to degrees
trigonometry PI() returns the value of the mathematical constant $\pi$, accurate to 14 decimal places
trigonometry RADIANS( angle )

radians = $\frac {180^0}{\pi}$

converts degrees to radians
trigonometry SEC( number )

$sec(\theta) = \frac {hyp}{adj} = csc \left ( \frac {\pi}{2} - \theta \right ) = \frac {1}{cos(\theta)}$

calculates the secant of an angle given in radians
trigonometry SECH( number )

$sech(x) = \frac {1}{cosh(x)} = \frac {2}{e^x + e^{-x}} = \frac {2e^x}{e^{2x} + 1} = \frac {2e^{-x}}{1 + e^{-2x}}$

calculates the hyperbolic secant of a real number given in radians
trigonometry SIN( number )

$sin(\theta) = \frac {opp}{hyp} = cos \left ( \frac {\pi}{2} - \theta \right ) = \frac {1}{csc(\theta)}$

calculates the sine of an angle given in radians
trigonometry SINH( number )

$sinh(x) = \frac {e^x - e^{-x}}{2} = \frac {e^{2x} - 1}{2e^x} = \frac {1 -e^{-2x}}{2e^{-x}} $

calculates the hyperbolic sine of a real number given in radians
trigonometry SQRTPI( number ) = SQRT( number * $pi$ ) returns the square root of a number multiplied by the mathematical constant $\pi$;
trigonometry TAN( number )

$tan(\theta) = \frac {opp}{adj} = \frac {sin(\theta)}{cos(\theta)} = cot \left ( \frac {\pi}{2} - \theta \right ) = \frac {1}{cot(\theta)}$

calculates the sine of an angle given in radians
trigonometry TANH( number )

$tanh(x) = \frac {sinh(x)}{cosh(x)} = \frac {e^x - e^{-x}}{e^x + e^{-x}} = \frac {e^{2x} - 1}{e^{2x} + 1} = \frac {1 - e^{-2x}}{1 + e^{-2x}}$

calculates the hyperbolic tangent (tanh) of a supplied number
time-date DATE( year, month, day ) converts a supplied year, month and day into an Excel date
time-date DATEVALUE( date_text ) converts a text representation of a date into an Excel date
time-date DAY( serial_number ) returns an integer representing the day of the month (from 1 - 31) of a supplied date
time-date DAYS( end_date, start_date ) returns the number of days between two supplied dates
time-date DAYS360( start_date, end_date, [method] ) returns the number of days between 2 dates, based on a 360-day year (12 x 30 months)
time-date EDATE( start_date, months ) returns a date that is a specified number of months before or after a supplied start date
time-date EOMONTH( start_date, months ) returns the last day of the month, that is a specified number of months before or after an initial supplied start date
time-date HOUR( serial_number ) returns an integer representing the hour component of a supplied Excel time
time-date ISOWEEKNUM( date ) returns the ISO week number of a supplied date
time-date MINUTE( serial_number ) returns an integer representing the minute component of a supplied Excel time
time-date MONTH( serial_number ) returns an integer, representing the month (from 1 - 12) of a supplied date
time-date NETWORKDAYS( start_date, end_date, [holidays] ) calculates the number of work days between two supplied dates (including the start and end date) and includes all weekdays (Mon - Fri), excluding a supplied list of holidays
time-date NOW() returns the current date and time
time-date SECOND( serial_number ) returns an integer representing the second component of a supplied Excel time
time-date TIME( hour, minute, second ) accepts three integer arguments representing hours, minutes and seconds, and returns an Excel time
time-date TIMEVALUE( time_text ) converts a text representation of a time, into an Excel time
time-date TODAY() returns the current date
time-date WEEKDAY( serial_number, [return_type] ) returns an integer representing the day of the week for a supplied date
time-date WEEKNUM( serial_number, [return_type] ) returns an integer representing the week number (from 1 to 53) of the year
time-date WORKDAY( start_date, days, [holidays] ) returns a date that is a supplied number of working days (excluding weekends and holidays) ahead of a given start date
time-date WORKDAY.INTL( start_date, days, [weekend], [holidays] ) returns a date that is a supplied number of working days (excluding weekends and holidays) ahead of a given start date
time-date YEAR( serial_number ) returns an integer representing the year of a supplied date
time-date YEARFRAC( start_date, end_date, [basis] ) returns the fraction of a year that is represented by the number of whole days between two supplied dates
error ERROR.TYPE( error_val ) receives an error value and returns an integer, that indicates the type of the supplied error
error IFERROR( value, value_if_error ) receives two values (or expressions) and tests if the first one evaluates to an error
error ISERR( value ) tests if a supplied expression or value returns any Excel error, except the #N/A error, if so, the function returns TRUE, if the value is not an error or is the #N/A error, returns FALSE
error ISERROR( value ) tests if an initial supplied expression (or value) returns an Excel error, and if so, returns TRUE, otherwise returns FALSE
error ISNA( value ) tests if an expression or value returns the Excel #N/A error, and if so, returns TRUE, otherwise returns FALSE
error NA() returns the Excel #N/A error produced when an Excel Formula is unable to find a value that it needs
logical AND( logical_test1, [logical_test2], ... ) tests a number of supplied conditions and returns TRUE if all of the conditions evaluate to TRUE or FALSE if any of the conditions evaluate to FALSE
logical FALSE() returns the logical value FALSE
logical IFS( logical_test1, value_if_true1, [logical_test2, value_if_true2], [logical_test3, value_if_true3], ... ) tests a number of supplied conditions and returns the result corresponding to the first condition that evaluates to TRUE
logical ISBLANK( value ) tests if a specified cell is blank (empty) and if so, returns TRUE, otherwise the function returns FALSE
logical ISEVEN( number ) tests if a numeric expression is even, and if so, returns TRUE, otherwise returns FALSE
logical ISFORMULA( reference ) tests if a specified cell contains a formula, and if so, returns TRUE; Otherwise, the function returns FALSE
logical ISLOGICAL( value ) tests if a supplied value or expression is TRUE or FALSE, if so, the function returns TRUE, otherwise, it returns FALSE
logical ISNONTEXT( value ) tests if a supplied value is text, if not, the function returns TRUE; If the supplied value is text, the function returns FALSE
logical ISNUMBER( value ) tests if a numeric expression is a number, if so returns TRUE, otherwise returns FALSE
logical ISODD( number ) tests if a numeric expression is odd, and if so, returns TRUE, otherwise returns FALSE
logical ISREF( value ) tests if a supplied value is a reference, if so, the function returns TRUE, otherwise it returns FALSE
logical ISTEXT( value ) tests if a supplied value is text, and if so, returns TRUE, otherwise, the function returns FALSE
logical NOT( logical ) returns the opposite to a supplied logical value
logical OR( logical_test1, [logical_test2], ... ) tests a number of supplied conditions and returns: TRUE if any of the conditions evaluate to TRUE or FALSE if all of the conditions evaluate to FALSE
logical TRUE() returns the logical value TRUE
logical XOR( logical_test1, [logical_test2], ... ) returns TRUE if an odd number of the supplied conditions evaluate to TRUE, and FALSE otherwise
sheet ADDRESS( row_num, column_num, [abs_num], [a1], [sheet_text] ) takes a row and a column number and returns a cell reference as a text string
sheet CELL( info_type, reference ) returns information about a given cell contents, formatting or location
sheet INDEX( array, row_num, [col_num] ) array form used to look up a reference to a cell within a single range
sheet INDEX( range, row_num, [col_num], [area_num] ) range form used to extract references from ranges that are made up of more than one area
sheet INDIRECT( ref_text, [a1] ) converts a text string into a cell reference
sheet INFO( type_text ) returns a text string containing information about the current operating environment
sheet OFFSET( reference, rows, cols, [height], [width] ) returns range of cells that is a specified number of rows and columns from an initial specified range
sheet SHEET( [value] ) returns the Sheet number for a specified reference
sheet SHEETS( [reference] ) returns the number of sheets in a supplied reference


Questions, comments, suggestions: Dr. Denise Meeks, email: tucsonkosmicgirl@gmail.com