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PHPExcel_Calculation_Statistical
AVERAGEIF(mixed $aArgs, string $condition, array $averageArgs = array()) : 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 | |
| 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 | |
| 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 http://support.microsoft.com/kb/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 |
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 |
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() : 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.
LINEST(mixed $yValues, mixed $xValues = NULL, mixed $const = TRUE, mixed $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.
| mixed | $yValues | |
| mixed | $xValues | |
| mixed | $const | |
| mixed | $stats |
LOGEST(mixed $yValues, mixed $xValues = null, mixed $const = True, mixed $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.
| mixed | $yValues | |
| mixed | $xValues | |
| mixed | $const | |
| mixed | $stats |
MAXIF(mixed $aArgs, string $condition, mixed $sumArgs = array()) : 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 | |
| string | $condition | The criteria that defines which cells will be checked. |
| mixed | $sumArgs |
MINIF(mixed $aArgs, string $condition, mixed $sumArgs = array()) : 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 | |
| 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 |
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 |
SKEW() : 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.
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
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 |