List of Excel Compatibility Functions with Syntax and Arguments

This reference table lists all officially documented Compatibility Functions. It is based on the Excel Help documentation and linked in each row when clicking on the function name. Export the table and/or display additional columns via the symbols to the top right of the table. Please report errors or inconsistencies via the comment function at the bottom of this page. Also check the main table with List of all Excel Functions.

#Excel FunctionDescriptionSyntax with ArgumentsSyntax onlyArguments only
1BETADISTReturns the cumulative beta probability density function=BETADIST(xx [required]: The value between A and B at which to evaluate the function., alphaalpha [required]: A parameter of the distribution., betabeta [required]: A parameter of the distribution., [aa [optional]: A lower bound to the interval of x.], [bb [optional]: An upper bound to the interval of x.])=BETADIST(x, alpha, beta, [a], [b])
  • x (required): The value between A and B at which to evaluate the function.
  • alpha (required): A parameter of the distribution.
  • beta (required): A parameter of the distribution.
  • a (optional): A lower bound to the interval of x.
  • b (optional): An upper bound to the interval of x.
2BETAINVReturns the inverse of the cumulative beta probability density function for a specified beta distribution=BETAINV(probabilityprobability [required]: A probability associated with the beta distribution., alphaalpha [required]: A parameter of the distribution., betabeta [required]: A parameter the distribution., [aa [optional]: A lower bound to the interval of x.], [bb [optional]: An upper bound to the interval of x.])=BETAINV(probability, alpha, beta, [a], [b])
  • probability (required): A probability associated with the beta distribution.
  • alpha (required): A parameter of the distribution.
  • beta (required): A parameter the distribution.
  • a (optional): A lower bound to the interval of x.
  • b (optional): An upper bound to the interval of x.
3BINOMDISTReturns the individual term binomial distribution probability=BINOMDIST(number_snumber_s [required]: The number of successes in trials., trialstrials [required]: The number of independent trials., probability_sprobability_s [required]: The probability of success on each trial., cumulativecumulative [required]: A logical value that determines the form of the function.)=BINOMDIST(number_s, trials, probability_s, cumulative)
  • number_s (required): The number of successes in trials.
  • trials (required): The number of independent trials.
  • probability_s (required): The probability of success on each trial.
  • cumulative (required): A logical value that determines the form of the function.
4CHIDISTReturns the right-tailed probability of the chi-squared distribution=CHIDIST(xx [required]: The value at which you want to evaluate the distribution., deg_freedomdeg_freedom [required]: The number of degrees of freedom.)=CHIDIST(x, deg_freedom)
  • x (required): The value at which you want to evaluate the distribution.
  • deg_freedom (required): The number of degrees of freedom.
5CHIINVReturns the inverse of the right-tailed probability of the chi-squared distribution=CHIINV(probabilityprobability [required]: A probability associated with the chi-squared distribution., deg_freedomdeg_freedom [required]: The number of degrees of freedom.)=CHIINV(probability, deg_freedom)
  • probability (required): A probability associated with the chi-squared distribution.
  • deg_freedom (required): The number of degrees of freedom.
6CHITESTReturns the test for independence=CHITEST(actual_rangeactual_range [required]: The range of data that contains observations to test against expected values., expected_rangeexpected_range [required]: The range of data that contains the ratio of the product of row totals and column totals to the grand total.)=CHITEST(actual_range, expected_range)
  • actual_range (required): The range of data that contains observations to test against expected values.
  • expected_range (required): The range of data that contains the ratio of the product of row totals and column totals to the grand total.
7CONFIDENCEReturns the confidence interval for a population mean, using a normal distribution=CONFIDENCE(alphaalpha [required]: The significance level used to compute the confidence level., standard_devstandard_dev [required]: The population standard deviation for the data range and is assumed to be known., sizesize [required]: The sample size.)=CONFIDENCE(alpha, standard_dev, size)
  • alpha (required): The significance level used to compute the confidence level.
  • standard_dev (required): The population standard deviation for the data range and is assumed to be known.
  • size (required): The sample size.
8COVARReturns covariance, the average of the products of deviations for each data point pair in two data sets=COVAR(array1array1 [required]: The first cell range of integers., array2array2 [required]: The second cell range of integers.)=COVAR(array1, array2)
  • array1 (required): The first cell range of integers.
  • array2 (required): The second cell range of integers.
9CRITBINOMReturns the smallest value for which the cumulative binomial distribution is greater than or equal to a criterion value=CRITBINOM(trialstrials [required]: The number of Bernoulli trials., probability_sprobability_s [required]: The probability of a success on each trial., alphaalpha [required]: The criterion value.)=CRITBINOM(trials, probability_s, alpha)
  • trials (required): The number of Bernoulli trials.
  • probability_s (required): The probability of a success on each trial.
  • alpha (required): The criterion value.
10EXPONDISTReturns the exponential distribution=EXPONDIST(xx [required]: The value of the function., lambdalambda [required]: The parameter value., cumulativecumulative [required]: A logical value that indicates which form of the exponential function to provide.)=EXPONDIST(x, lambda, cumulative)
  • x (required): The value of the function.
  • lambda (required): The parameter value.
  • cumulative (required): A logical value that indicates which form of the exponential function to provide.
11FDISTReturns the F probability distribution (degree of diversity) for two data sets=FDIST(xx [required]: The value at which to evaluate the function., deg_freedom1deg_freedom1 [required]: The numerator degrees of freedom., deg_freedom2deg_freedom2 [required]: The denominator degrees of freedom.)=FDIST(x, deg_freedom1, deg_freedom2)
  • x (required): The value at which to evaluate the function.
  • deg_freedom1 (required): The numerator degrees of freedom.
  • deg_freedom2 (required): The denominator degrees of freedom.
12FLOORRounds number down, toward zero, to the nearest multiple of significance=FLOOR(numbernumber [required]: The numeric value you want to round., significancesignificance [required]: The multiple to which you want to round.)=FLOOR(number, significance)
  • number (required): The numeric value you want to round.
  • significance (required): The multiple to which you want to round.
13FTESTReturns the result of an F-test, the two-tailed probability that the variances in array1 and array2 are not significantly different=FTEST(array1array1 [required]: The first array or range of data., array2array2 [required]: The second array or range of data.)=FTEST(array1, array2)
  • array1 (required): The first array or range of data.
  • array2 (required): The second array or range of data.
14GAMMADISTReturns the gamma distribution=GAMMADIST(xx [required]: The value at which you want to evaluate the distribution., alphaalpha [required]: A parameter to the distribution., betabeta [required]: A parameter to the distribution., cumulativecumulative [required]: A logical value that determines the form of the function.)=GAMMADIST(x, alpha, beta, cumulative)
  • x (required): The value at which you want to evaluate the distribution.
  • alpha (required): A parameter to the distribution.
  • beta (required): A parameter to the distribution.
  • cumulative (required): A logical value that determines the form of the function.
15GAMMAINVReturns the inverse of the gamma cumulative distribution=GAMMAINV(probabilityprobability [required]: The probability associated with the gamma distribution., alphaalpha [required]: A parameter to the distribution., betabeta [required]: A parameter to the distribution.)=GAMMAINV(probability, alpha, beta)
  • probability (required): The probability associated with the gamma distribution.
  • alpha (required): A parameter to the distribution.
  • beta (required): A parameter to the distribution.
16HYPGEOMDISTReturns the hypergeometric distribution/ probability of a given number of sample successes, given the sample size, population successes, and population size. =HYPGEOMDIST(sample_ssample_s [required]: The number of successes in the sample., number_samplenumber_sample [required]: The size of the sample., population_spopulation_s [required]: The number of successes in the population., number_popnumber_pop [required]: The population size.)=HYPGEOMDIST(sample_s, number_sample, population_s, number_pop)
  • sample_s (required): The number of successes in the sample.
  • number_sample (required): The size of the sample.
  • population_s (required): The number of successes in the population.
  • number_pop (required): The population size.
17LOGINVReturns the inverse of the lognormal cumulative distribution function of x, where ln(x) is normally distributed with parameters mean and standard_dev. =LOGINV(probabilityprobability [required]: A probability associated with the lognormal distribution., meanmean [required]: The mean of ln(x)., standard_devstandard_dev [required]: The standard deviation of ln(x).)=LOGINV(probability, mean, standard_dev)
  • probability (required): A probability associated with the lognormal distribution.
  • mean (required): The mean of ln(x).
  • standard_dev (required): The standard deviation of ln(x).
18LOGNORMDISTReturns the cumulative lognormal distribution of x, where ln(x) is normally distributed with parameters mean and standard_dev=LOGNORMDIST(xx [required]: The value at which to evaluate the function., meanmean [required]: The mean of ln(x)., standard_devstandard_dev [required]: The standard deviation of ln(x).)=LOGNORMDIST(x, mean, standard_dev)
  • x (required): The value at which to evaluate the function.
  • mean (required): The mean of ln(x).
  • standard_dev (required): The standard deviation of ln(x).
19MODEReturns the most frequently occurring, or repetitive, value in an array or range of data=MODE(number1number1 [required]: The first number argument for which you want to calculate the mode., [number2number2 [optional]: Additional numbers to calculate the mode.], ...)=MODE(number1, [number2], ...)
  • number1 (required): The first number argument for which you want to calculate the mode.
  • number2 (optional): Additional numbers to calculate the mode.
20NEGBINOMDISTReturns the negative binomial distribution=NEGBINOMDIST(number_fnumber_f [required]: The number of failures., number_snumber_s [required]: The threshold number of successes., probability_sprobability_s [required]: The probability of a success.)=NEGBINOMDIST(number_f, number_s, probability_s)
  • number_f (required): The number of failures.
  • number_s (required): The threshold number of successes.
  • probability_s (required): The probability of a success.
21NORM.INVReturns the inverse of the normal cumulative distribution for the specified mean and standard deviation=NORM.INV(probabilityprobability [required]: A probability corresponding to the normal distribution., meanmean [required]: The arithmetic mean of the distribution., standard_devstandard_dev [required]: The standard deviation of the distribution.)=NORM.INV(probability, mean, standard_dev)
  • probability (required): A probability corresponding to the normal distribution.
  • mean (required): The arithmetic mean of the distribution.
  • standard_dev (required): The standard deviation of the distribution.
22NORMDISTReturns the normal distribution for the specified mean and standard deviation=NORMDIST(xx [required]: The value for which you want the distribution., meanmean [required]: The arithmetic mean of the distribution., standard_devstandard_dev [required]: The standard deviation of the distribution., cumulativecumulative [required]: A logical value that determines the form of the function.)=NORMDIST(x, mean, standard_dev, cumulative)
  • x (required): The value for which you want the distribution.
  • mean (required): The arithmetic mean of the distribution.
  • standard_dev (required): The standard deviation of the distribution.
  • cumulative (required): A logical value that determines the form of the function.
23NORMSDISTReturns the standard normal cumulative distribution function=NORMSDIST(zz [required]: The value for which you want the distribution.)=NORMSDIST(z)
  • z (required): The value for which you want the distribution.
24NORMSINVReturns the inverse of the standard normal cumulative distribution=NORMSINV(probabilityprobability [required]: A probability corresponding to the normal distribution.)=NORMSINV(probability)
  • probability (required): A probability corresponding to the normal distribution.
25PERCENTILEReturns the k-th percentile of values in a range=PERCENTILE(arrayarray [required]: The array or range of data that defines relative standing., kk [required]: The percentile value in the range 0.)=PERCENTILE(array, k)
  • array (required): The array or range of data that defines relative standing.
  • k (required): The percentile value in the range 0.
26PERCENTRANKReturns the rank of a value in a data set as a percentage of the data set=PERCENTRANK(arrayarray [required]: The array or range of data with numeric values that defines relative standing., xx [required]: The value for which you want to know the rank., [significancesignificance [optional]: A value that identifies the number of significant digits for the returned percentage value.])=PERCENTRANK(array, x, [significance])
  • array (required): The array or range of data with numeric values that defines relative standing.
  • x (required): The value for which you want to know the rank.
  • significance (optional): A value that identifies the number of significant digits for the returned percentage value.
27POISSONReturns the Poisson distribution=POISSON(xx [required]: The number of events., meanmean [required]: The expected numeric value., cumulativecumulative [required]: A logical value that determines the form of the probability distribution returned.)=POISSON(x, mean, cumulative)
  • x (required): The number of events.
  • mean (required): The expected numeric value.
  • cumulative (required): A logical value that determines the form of the probability distribution returned.
28QUARTILEReturns the quartile of a data set=QUARTILE(arrayarray [required]: The array or cell range of numeric values for which you want the quartile value., quartquart [required]: Indicates which value to return.)=QUARTILE(array, quart)
  • array (required): The array or cell range of numeric values for which you want the quartile value.
  • quart (required): Indicates which value to return.
29RANKReturns the rank of a number in a list of numbers=RANK(numbernumber [required]: The number whose rank you want to find., refref [required]: An array of, or a reference to, a list of numbers., [orderorder [optional]: A number specifying how to rank number.])=RANK(number, ref, [order])
  • number (required): The number whose rank you want to find.
  • ref (required): An array of, or a reference to, a list of numbers.
  • order (optional): A number specifying how to rank number.
30STDEVEstimates standard deviation based on a sample=STDEV(number1number1 [required]: The first number argument corresponding to a sample of a population., [number2number2 [optional]: Additional numbers to a sample of a population], ...)=STDEV(number1, [number2], ...)
  • number1 (required): The first number argument corresponding to a sample of a population.
  • number2 (optional): Additional numbers to a sample of a population
31STDEVPCalculates standard deviation based on the entire population given as arguments=STDEVP(number1number1 [required]: The first number argument corresponding to a population., [number2number2 [optional]: Additional optional numbers], ...)=STDEVP(number1, [number2], ...)
  • number1 (required): The first number argument corresponding to a population.
  • number2 (optional): Additional optional numbers
32TDISTReturns the Percentage Points (probability) for the Student t-distribution where a numeric value (x) is a calculated value of t for which the Percentage Points are to be computed=TDIST(xx [required]: The numeric value at which to evaluate the distribution., deg_freedomdeg_freedom [required]: An integer indicating the number of degrees of freedom., tailstails [required]: Specifies the number of distribution tails to return.)=TDIST(x, deg_freedom, tails)
  • x (required): The numeric value at which to evaluate the distribution.
  • deg_freedom (required): An integer indicating the number of degrees of freedom.
  • tails (required): Specifies the number of distribution tails to return.
33TINVReturns the two-tailed inverse of the Student's t-distribution=TINV(probabilityprobability [required]: The probability associated with the two-tailed Student's t-distribution., deg_freedomdeg_freedom [required]: The number of degrees of freedom with which to characterize the distribution.)=TINV(probability, deg_freedom)
  • probability (required): The probability associated with the two-tailed Student's t-distribution.
  • deg_freedom (required): The number of degrees of freedom with which to characterize the distribution.
34TTESTReturns the probability associated with a Student's t-Test. =TTEST(array1array1 [required]: The first data set., array2array2 [required]: The second data set., tailstails [required]: Specifies the number of distribution tails., typetype [required]: The kind of t-Test to perform.)=TTEST(array1, array2, tails, type)
  • array1 (required): The first data set.
  • array2 (required): The second data set.
  • tails (required): Specifies the number of distribution tails.
  • type (required): The kind of t-Test to perform.
35VAREstimates variance based on a sample=VAR(number1number1 [required]: The first number argument corresponding to a sample of a population., [number2number2 [optional]: Additional optional numbers.], ...)=VAR(number1, [number2], ...)
  • number1 (required): The first number argument corresponding to a sample of a population.
  • number2 (optional): Additional optional numbers.
36VARPCalculates variance based on the entire population=VARP(number1number1 [required]: The first number argument corresponding to a population., [number2number2 [optional]: Additional optional numbers.], ...)=VARP(number1, [number2], ...)
  • number1 (required): The first number argument corresponding to a population.
  • number2 (optional): Additional optional numbers.
37WEIBULLReturns the Weibull distribution=WEIBULL(xx [required]: The value at which to evaluate the function., alphaalpha [required]: A parameter to the distribution., betabeta [required]: A parameter to the distribution., cumulativecumulative [required]: Determines the form of the function.)=WEIBULL(x, alpha, beta, cumulative)
  • x (required): The value at which to evaluate the function.
  • alpha (required): A parameter to the distribution.
  • beta (required): A parameter to the distribution.
  • cumulative (required): Determines the form of the function.
38ZTESTReturns the one-tailed P-value of a z-test=ZTEST(arrayarray [required]: The array or range of data against which to test x., xx [required]: The value to test., [sigmasigma [optional]: The population (known) standard deviation.])=ZTEST(array, x, [sigma])
  • array (required): The array or range of data against which to test x.
  • x (required): The value to test.
  • sigma (optional): The population (known) standard deviation.

Created by admin on 2/9/2021

 

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