LOG_GAMMA_X_MAX_VALUE
LOG_GAMMA_X_MAX_VALUE = 2.55E+305
AVERAGEIF(mixed $aArgs, string $condition, array $averageArgs = []) : float
AVERAGEIF.
Returns the average value from a range of cells that contain numbers within the list of arguments
Excel Function: AVERAGEIF(value1[,value2[, ...]],condition)
| mixed | $aArgs | Data values |
| string | $condition | the criteria that defines which cells will be checked |
| array | $averageArgs | Data values |
BETADIST(float $value, float $alpha, float $beta, mixed $rMin, mixed $rMax = 1) : float
BETADIST.
Returns the beta distribution.
| float | $value | Value at which you want to evaluate the distribution |
| float | $alpha | Parameter to the distribution |
| float | $beta | Parameter to the distribution |
| mixed | $rMin | |
| mixed | $rMax |
BETAINV(float $probability, float $alpha, float $beta, float $rMin, float $rMax = 1) : float
BETAINV.
Returns the inverse of the beta distribution.
| float | $probability | Probability at which you want to evaluate the distribution |
| float | $alpha | Parameter to the distribution |
| float | $beta | Parameter to the distribution |
| float | $rMin | Minimum value |
| float | $rMax | Maximum value |
BINOMDIST(float $value, float $trials, float $probability, bool $cumulative) : float
BINOMDIST.
Returns the individual term binomial distribution probability. Use BINOMDIST in problems with a fixed number of tests or trials, when the outcomes of any trial are only success or failure, when trials are independent, and when the probability of success is constant throughout the experiment. For example, BINOMDIST can calculate the probability that two of the next three babies born are male.
| float | $value | Number of successes in trials |
| float | $trials | Number of trials |
| float | $probability | Probability of success on each trial |
| bool | $cumulative |
COUNTIF(mixed $aArgs, string $condition) : int
COUNTIF.
Counts the number of cells that contain numbers within the list of arguments
Excel Function: COUNTIF(value1[,value2[, ...]],condition)
| mixed | $aArgs | Data values |
| string | $condition | the criteria that defines which cells will be counted |
CRITBINOM(float $trials, float $probability, float $alpha) : int
CRITBINOM.
Returns the smallest value for which the cumulative binomial distribution is greater than or equal to a criterion value
See https://support.microsoft.com/en-us/help/828117/ for details of the algorithm used
| float | $trials | number of Bernoulli trials |
| float | $probability | probability of a success on each trial |
| float | $alpha | criterion value |
EXPONDIST(float $value, float $lambda, bool $cumulative) : float
EXPONDIST.
Returns the exponential distribution. Use EXPONDIST to model the time between events, such as how long an automated bank teller takes to deliver cash. For example, you can use EXPONDIST to determine the probability that the process takes at most 1 minute.
| float | $value | Value of the function |
| float | $lambda | The parameter value |
| bool | $cumulative |
FORECAST(float $xValue, mixed $yValues, mixed $xValues) : float
FORECAST.
Calculates, or predicts, a future value by using existing values. The predicted value is a y-value for a given x-value.
| float | $xValue | Value of X for which we want to find Y |
| mixed | $yValues | array of mixed Data Series Y |
| mixed | $xValues | of mixed Data Series X |
GAMMADIST(float $value, float $a, float $b, bool $cumulative) : float
GAMMADIST.
Returns the gamma distribution.
| float | $value | Value at which you want to evaluate the distribution |
| float | $a | Parameter to the distribution |
| float | $b | Parameter to the distribution |
| bool | $cumulative |
GAMMAINV(float $probability, float $alpha, float $beta) : float
GAMMAINV.
Returns the inverse of the beta distribution.
| float | $probability | Probability at which you want to evaluate the distribution |
| float | $alpha | Parameter to the distribution |
| float | $beta | Parameter to the distribution |
GEOMEAN(mixed ...$args) : float
GEOMEAN.
Returns the geometric mean of an array or range of positive data. For example, you can use GEOMEAN to calculate average growth rate given compound interest with variable rates.
Excel Function: GEOMEAN(value1[,value2[, ...]])
| mixed | $args variadic | Data values |
GROWTH(array $yValues, array $xValues = [], array $newValues = [], bool $const = true) : array
GROWTH.
Returns values along a predicted emponential Trend
| array | $yValues | Data Series Y |
| array | $xValues | Data Series X |
| array | $newValues | Values of X for which we want to find Y |
| bool | $const | a logical value specifying whether to force the intersect to equal 0 |
of float
HYPGEOMDIST(float $sampleSuccesses, float $sampleNumber, float $populationSuccesses, float $populationNumber) : float
HYPGEOMDIST.
Returns the hypergeometric distribution. HYPGEOMDIST returns the probability of a given number of sample successes, given the sample size, population successes, and population size.
| float | $sampleSuccesses | Number of successes in the sample |
| float | $sampleNumber | Size of the sample |
| float | $populationSuccesses | Number of successes in the population |
| float | $populationNumber | Population size |
KURT(array ...$args) : float
KURT.
Returns the kurtosis of a data set. Kurtosis characterizes the relative peakedness or flatness of a distribution compared with the normal distribution. Positive kurtosis indicates a relatively peaked distribution. Negative kurtosis indicates a relatively flat distribution.
| array | $args variadic | Data Series |
LINEST(array $yValues, null|array $xValues = null, bool $const = true, bool $stats = false) : array
LINEST.
Calculates the statistics for a line by using the "least squares" method to calculate a straight line that best fits your data, and then returns an array that describes the line.
| array | $yValues | Data Series Y |
| null|array | $xValues | Data Series X |
| bool | $const | a logical value specifying whether to force the intersect to equal 0 |
| bool | $stats | a logical value specifying whether to return additional regression statistics |
LOGEST(array $yValues, null|array $xValues = null, bool $const = true, bool $stats = false) : array
LOGEST.
Calculates an exponential curve that best fits the X and Y data series, and then returns an array that describes the line.
| array | $yValues | Data Series Y |
| null|array | $xValues | Data Series X |
| bool | $const | a logical value specifying whether to force the intersect to equal 0 |
| bool | $stats | a logical value specifying whether to return additional regression statistics |
MAXIF(mixed $aArgs, string $condition, mixed $sumArgs = []) : float
MAXIF.
Counts the maximum value within a range of cells that contain numbers within the list of arguments
Excel Function: MAXIF(value1[,value2[, ...]],condition)
| mixed | $aArgs | Data values |
| string | $condition | the criteria that defines which cells will be checked |
| mixed | $sumArgs |
MINIF(mixed $aArgs, string $condition, mixed $sumArgs = []) : float
MINIF.
Returns the minimum value within a range of cells that contain numbers within the list of arguments
Excel Function: MINIF(value1[,value2[, ...]],condition)
| mixed | $aArgs | Data values |
| string | $condition | the criteria that defines which cells will be checked |
| mixed | $sumArgs |
NEGBINOMDIST(float $failures, float $successes, float $probability) : float
NEGBINOMDIST.
Returns the negative binomial distribution. NEGBINOMDIST returns the probability that there will be number_f failures before the number_s-th success, when the constant probability of a success is probability_s. This function is similar to the binomial distribution, except that the number of successes is fixed, and the number of trials is variable. Like the binomial, trials are assumed to be independent.
| float | $failures | Number of Failures |
| float | $successes | Threshold number of Successes |
| float | $probability | Probability of success on each trial |
NORMDIST(float $value, float $mean, float $stdDev, bool $cumulative) : float
NORMDIST.
Returns the normal distribution for the specified mean and standard deviation. This function has a very wide range of applications in statistics, including hypothesis testing.
| float | $value | |
| float | $mean | Mean Value |
| float | $stdDev | Standard Deviation |
| bool | $cumulative |
PERCENTRANK(float[] $valueSet, int $value, int $significance = 3) : float
PERCENTRANK.
Returns the rank of a value in a data set as a percentage of the data set.
| float[] | $valueSet | An array of, or a reference to, a list of numbers |
| int | $value | the number whose rank you want to find |
| int | $significance | the number of significant digits for the returned percentage value |
PERMUT(int $numObjs, int $numInSet) : int
PERMUT.
Returns the number of permutations for a given number of objects that can be selected from number objects. A permutation is any set or subset of objects or events where internal order is significant. Permutations are different from combinations, for which the internal order is not significant. Use this function for lottery-style probability calculations.
| int | $numObjs | Number of different objects |
| int | $numInSet | Number of objects in each permutation |
Number of permutations
POISSON(float $value, float $mean, bool $cumulative) : float
POISSON.
Returns the Poisson distribution. A common application of the Poisson distribution is predicting the number of events over a specific time, such as the number of cars arriving at a toll plaza in 1 minute.
| float | $value | |
| float | $mean | Mean Value |
| bool | $cumulative |
RANK(int $value, float[] $valueSet, int $order) : float
RANK.
Returns the rank of a number in a list of numbers.
| int | $value | the number whose rank you want to find |
| float[] | $valueSet | An array of, or a reference to, a list of numbers |
| int | $order | Order to sort the values in the value set |
SKEW(array ...$args) : float
SKEW.
Returns the skewness of a distribution. Skewness characterizes the degree of asymmetry of a distribution around its mean. Positive skewness indicates a distribution with an asymmetric tail extending toward more positive values. Negative skewness indicates a distribution with an asymmetric tail extending toward more negative values.
| array | $args variadic | Data Series |
STANDARDIZE(float $value, float $mean, float $stdDev) : float
STANDARDIZE.
Returns a normalized value from a distribution characterized by mean and standard_dev.
| float | $value | Value to normalize |
| float | $mean | Mean Value |
| float | $stdDev | Standard Deviation |
Standardized value
STDEV(mixed ...$args) : float
STDEV.
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).
Excel Function: STDEV(value1[,value2[, ...]])
| mixed | $args variadic | Data values |
TREND(array $yValues, array $xValues = [], array $newValues = [], bool $const = true) : array
TREND.
Returns values along a linear Trend
| array | $yValues | Data Series Y |
| array | $xValues | Data Series X |
| array | $newValues | Values of X for which we want to find Y |
| bool | $const | a logical value specifying whether to force the intersect to equal 0 |
of float
TRIMMEAN(mixed ...$args) : float
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.
Excel Function: TRIMEAN(value1[,value2[, ...]], $discard)
| mixed | $args variadic | Data values |
WEIBULL(float $value, float $alpha, float $beta, bool $cumulative) : float
WEIBULL.
Returns the Weibull distribution. Use this distribution in reliability analysis, such as calculating a device's mean time to failure.
| float | $value | |
| float | $alpha | Alpha Parameter |
| float | $beta | Beta Parameter |
| bool | $cumulative |
ZTEST(float $dataSet, float $m0, float $sigma = null) : float
ZTEST.
Returns the Weibull distribution. Use this distribution in reliability analysis, such as calculating a device's mean time to failure.
| float | $dataSet | |
| float | $m0 | Alpha Parameter |
| float | $sigma | Beta Parameter |