[ ] indicates optional parameters
AVEDEV(number1, [number2, ...])AVEDEV(number1, [number2, ...])
Returns the average of the differences of a set of numbers from their mean.
number1, ... | The numbers of which you want the average deviation. |
AVERAGE(number1, [number2, ...])
Returns the average of a set of numbers.
number1, ... | The numbers of which you want the average. |
AVERAGEA(value1, [value2, ...])
Returns the average of a set of values.
value1, ... | The values of which you want the average. |
BETADIST(x, alpha, beta, [A], [B])
Returns the cumulative beta distribution probability.
x | The value at which you want to evaluate the function. |
alpha | The alpha value. |
beta | The beta value. |
A | The lower limit. If this parameter is omitted it defaults to 0. |
B | The upper limit. If this parameter is omitted it defaults to 1. |
BETAINV(probability, alpha, beta, [A], [B])
Returns the value associated with the specified cumulative beta distribution probability.
probability | The cumulative beta distribution probability for which you want the value. |
alpha | The alpha value. |
beta | The beta value. |
A | The lower limit. If this parameter is omitted it defaults to 0. |
B | The upper limit. If this parameter is omitted it defaults to 1. |
BINOMDIST(number_successes, trials, probability, cumulative)
Returns the binomial distribution probability.
number_successes | The number of trials that are successful. | ||||
trials | The total number of trials. | ||||
probability | The probability of a single trial being successful. | ||||
cumulative | Specifies whether to return the cumulative probability or not. The possible values are: | ||||
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Returns the chi-squared distribution probability.
x | The value at which you want to evaluate the function. |
degrees_freedom | The number of degrees of freedom. |
CHIINV(probability, degrees_freedom)
Returns the value associated with the specified chi-squared distribution probability.
probability | The probability for which you want the value. |
degrees_freedom | The number of degrees of freedom. |
CHITEST(actual_range, expected_range)
Returns the probability result of the chi-squared test.
actual_range | An array or reference to cells containing the empirical results. |
expected_range | An array or reference to cells containing the theoretical results. |
CONFIDENCE(alpha, standard_deviation, size)
Returns the confidence interval for a population mean.
alpha | The significance level. |
standard_deviation | The population standard deviation. |
size | The sample size. |
Returns the correlation coefficient of two ranges.
range1 | The first range to be compared. |
range2 | The second range to be compared. |
Returns the count of numbers in a list.
value1, ... | The items whose numbers are to be counted. |
Returns the count of values in a list.
value1, ... | The items whose values are to be counted. |
Returns the covariance of two ranges.
range1 | The first range to be compared. |
range2 | The second range to be compared. |
CRITBINOM(trials, probability_s, alpha)
Returns the value at which the cumulative binomial distribution is greater than or equal to alpha.
trials | The total number of trials. |
probability_s | The probability of a single trial being successful. |
alpha | The value at which you want to evaluate the function. |
DEVSQ(number1, [number2, ...])
Returns the sum of the squares of the differences of a set of numbers from their mean.
number1, ... | The numbers of which you want the squared deviations. |
EXPONDIST(x, lambda, cumulative)
Returns the exponential distribution probability.
x | The value at which you want to evaluate the function. | ||||
lambda | The lambda value. | ||||
cumulative | Specifies whether to return the cumulative probability or not. The possible values are: | ||||
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FDIST(x, degrees_freedom1, degrees_freedom2)
Returns the F distribution probability.
x | The value at which you want to evaluate the function. |
degrees_freedom1 | The degrees of freedom of the first set. |
degrees_freedom2 | The degrees of freedom of the second set. |
FINV(probability, degrees_freedom1, degrees_freedom2)
Returns the value associated with the specified F distribution probability.
probability | The probability for which you want the value. |
degrees_freedom1 | The degrees of freedom of the first set. |
degrees_freedom2 | The degrees of freedom of the second set. |
Returns the Fisher transformation.
x | The value at which to evaluate the function. |
Returns the inverse Fisher transformation.
y | The value at which to evaluate the function. |
FORECAST(x, known_ys, known_xs)
Returns the expected value of y for a given x value for a line passing through a specified set of points.
x | The x value at which to evaluate the function. |
known_ys | An array or reference to a range of cells containing the y values that are already known. |
known_xs | An array or reference to a range of cells containing the x values that are already known. |
FREQUENCY(data_array, bins_array)
Returns the counts of items in specified numeric categories.
data_array | An array or reference to a range of cells containing values to be counted. |
bins_array | An array or reference to a range of cells containing the upper limits for each category. |
Returns the probability result of the F test.
array1 | The first range to be compared. |
array2 | The second range to be compared. |
GAMMADIST(x, alpha, beta, cumulative)
Returns the gamma distribution probability.
x | The value at which you want to evaluate the function. | ||||
alpha | The alpha value. | ||||
beta | The beta value. | ||||
cumulative | Specifies whether to return the cumulative probability or not. The possible values are: | ||||
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GAMMAINV(probability, alpha, beta)
Returns the value associated with the specified gamma distribution probability.
probability | The probability for which you want the value. |
alpha | The alpha value. |
beta | The beta value. |
Returns the natural logarithm of the gamma function evaluated at x.
x | The value at which you want to evaluate the function. |
GEOMEAN(number1, [number2, ...])
Returns the geometric mean of a set of numbers.
number1, ... | The numbers of which you want the geometric mean. |
GROWTH(known_ys, [known_xs], [new_xs], [const])
Returns the expected values of y for given x values for an exponential curve passing through a specified set of points.
known_ys | The y values that are already known. | ||||
known_xs | The x values that are already known. If this parameter is omitted it defaults to an array of values from 1 to the number of known ys. | ||||
new_xs | The new x values for which y values are required. If this parameter is omitted it defaults to the known xs. | ||||
const | Specifies whether the line must pass through the origin. The possible values are: | ||||
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If this parameter is omitted it defaults to TRUE. |
HARMEAN(number1, [number2, ...])
Returns the harmonic mean of a set of numbers.
number1, ... | The numbers of which you want the harmonic mean. |
HYPGEOMDIST(sample_s, number_sample, population_s, number_population)
Returns the hypergeometric distribution probability.
sample_s | The number of sample trials that are successful. |
number_sample | The total number of trials in the sample. |
population_s | The number of population trials that are successful. |
number_population | The total number of trials in the population. |
Returns the expected value of y when x is zero for a line passing though a specified set of points.
y_range | The y values that are already known. |
x_range | The x values that are already known. |
Returns the kurtosis of a set of numbers.
number1, ... | The numbers of which you want the kurtosis. |
Returns the kth largest number in a set of numbers.
array | An array or reference to cells containing numbers of which you want the kth largest. |
k | The rank of the number that you want. |
LINEST(known_ys, [known_xs], [const], [stats])
Returns the coefficients for a straight line using multiple linear regression.
known_ys | The y values that are already known. | ||||
known_xs | One or more sets of x values corresponding to the known y values. If this parameter is omitted it defaults to an array of values from 1 to the number of known ys. | ||||
const | Specifies whether the line must pass through the origin. The possible values are: | ||||
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If this parameter is omitted it defaults to TRUE. | |||||
stats | Specifies whether the additional statistics are returned in the rows below the coefficients. These are: the standard error values for the coefficients, the R2 coefficient, the standard error for the Y estimate, the F statistic, the degrees of freedom, the regression sum of squares and the residual sum of squares. The possible values are: | ||||
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If this parameter is omitted it defaults to FALSE. |
LOGEST(known_ys, [known_xs], [const], [stats])
Returns the coefficients for an exponential curve using multiple linear regression.
known_ys | The y values that are already known. | ||||
known_xs | One or more sets of x values corresponding to the known y values. If this parameter is omitted it defaults to an array of values from 1 to the number of known ys. | ||||
const | Specifies whether the line must pass through the origin. The possible values are: | ||||
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If this parameter is omitted it defaults to TRUE. | |||||
stats | Specifies whether the additional statistics are returned in the rows below the coefficients. These are: the standard error values for the coefficients, the R2 coefficient, the standard error for the Y estimate, the F statistic, the degrees of freedom, the regression sum of squares and the residual sum of squares. The possible values are: | ||||
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If this parameter is omitted it defaults to FALSE. |
LOGINV(probability, mean, standard_dev)
Returns the value associated with the specified cumulative lognormal distribution probability.
probability | The probability for which you want the value. |
mean | The mean of the natural logarithms of the values. |
standard_dev | The standard deviation of the natural logarithms of the values. |
LOGNORMDIST(x, mean, standard_dev)
Returns the cumulative lognormal distribution probability.
x | The value at which you want to evaluate the function. |
mean | The mean of the natural logarithms of the values. |
standard_dev | The standard deviation of the natural logarithms of the values. |
Returns the maximum of a set of numbers.
number1, ... | The numbers of which you want the maximum. |
Returns the maximum of a set of values.
value1, ... | The values of which you want the maximum. |
MEDIAN(number1, [number2, ...])
Returns the median of a set of numbers.
number1, ... | The numbers of which you want the median. |
Returns the minimum of a set of numbers.
number1, ... | The numbers of which you want the minimum. |
Returns the minimum of a set of values.
value1, ... | The values of which you want the minimum. |
Returns the mode of a set of numbers.
number1, ... | The numbers of which you want the mode. |
NEGBINOMDIST(number_f, number_s, probability_s)
Returns the negative binomial distribution probability.
number_f | The number of trials that fail. |
number_s | The threshold number of trials that are successful. |
probability_s | The probability of a single trial being successful. |
NORMDIST(x, mean, standard_dev, cumulative)
Returns the normal distribution probability.
x | The value at which you want to evaluate the function. | ||||
mean | The mean of the values. | ||||
standard_dev | The standard deviation of the values. | ||||
cumulative | Specifies whether to return the cumulative probability or not. The possible values are: | ||||
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NORMINV(probability, mean, standard_dev)
Returns the value associated with the specified cumulative normal distribution probability.
probability | The probability for which you want the value. |
mean | The mean of the values. |
standard_dev | The standard deviation of the values. |
Returns the cumulative standard normal distribution probability.
z | The value at which you want to evaluate the function. |
Returns the value associated with the specified cumulative standard normal distribution probability.
probability | The probability for which you want the value. |
Returns the Pearson correlation coefficient.
array1 | The first range to be compared. |
array2 | The second range to be compared. |
Returns the kth percentile of a set of values.
array | An array or reference to cells containing the values. |
k | The percentile value. |
PERCENTRANK(array, x, [significance])
Returns the percentile of a value in a set of values.
array | An array or reference to cells containing the values. |
x | The value of which you want the percentile. |
significance | The number of decimal places required in the result. If this parameter is omitted it defaults to 3. |
Returns the number of permutations in which a number of items can be chosen from a total number.
number | The total number of items. |
number_chosen | The number of items chosen. |
Returns the Poisson distribution probability.
x | The value at which you want to evaluate the function. | ||||
mean | The mean of the values. | ||||
cumulative | Specifies whether to return the cumulative probability or not. The possible values are: | ||||
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PROB(x_range, prob_range, lower_limit, [upper_limit])
Returns the probability that numbers in a set are between the specified limits.
x_range | An array or reference to cells containing the numbers. |
prob_range | An array or reference to cells containing the probabilities associated with each number. These values must add up to 1. |
lower_limit | The lower limit of the test. |
upper_limit | The upper limit of the test. If this value is omitted it defaults to the value specified for the lower limit. |
Returns the specified quartile of a set of numbers.
array | An array or reference to cells containing the numbers. | ||||||||||
quart | Specifies which quartile to return. The possible values are: | ||||||||||
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Returns the rank of a number in a set of numbers.
number | The number of which you want the rank. | ||||
range | An array or reference to cells containing the values. | ||||
order | Specifies whether the list is treated as being in ascending or descending order of value. The possible values are: | ||||
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If this parameter is omitted it defaults to 0. |
Returns the square of the Pearson correlation coefficient.
y_array | The first range to be compared. |
x_array | The second range to be compared. |
Returns the skewness of a set of numbers.
number1, ... | The numbers of which you want the skewness. |
Returns the slope of a line passing through a specified set of points.
y_range | The y values that are already known. |
x_range | The x values that are already known. |
Returns the kth smallest number in a set of numbers.
array | An array or reference to cells containing numbers of which you want the kth smallest. |
k | The rank of the number that you want. |
STANDARDIZE(x, mean, standard_dev)
Returns the standardized value of x for the specified mean and standard deviation.
x | The value that you want to standardize. |
mean | The mean of the values. |
standard_dev | The standard deviation of the values. |
STDEV(number1, [number2, ...])
Returns the standard deviation (based on a population sample) of a set of numbers.
number1, ... | The numbers of which you want the standard deviation. |
Returns the standard deviation (based on a population sample) of a set of values.
value1, ... | The values of which you want the standard deviation. |
STDEVP(number1, [number2, ...])
Returns the standard deviation (based on the entire population) of a set of numbers.
number1, ... | The numbers of which you want the standard deviation. |
STDEVPA(value1, [value2, ...])
Returns the standard deviation (based on the entire population) of a set of values.
value1, ... | The values of which you want the standard deviation. |
Returns the standard error of the y values of a line passing through a specified set of points.
y_range | The y values that are already known. |
x_range | The x values that are already known. |
TDIST(x, degrees_freedom, tails)
Returns the Student's T distribution probability.
x | The value at which you want to evaluate the function. |
degrees_freedom | The degrees of freedom. |
tails | Specifies the tails to include in the distribution. Should be 1 or 2. |
TINV(probability, degrees_freedom)
Returns the value associated with the specified Student's T distribution probability.
probability | The probability for which you want the value. |
degrees_freedom | The degrees of freedom. |
TREND(known_ys, [known_xs], [new_xs], [const])
Returns the expected values of y for given x values for a line passing through a specified set of points.
known_ys | The y values that are already known. | ||||
known_xs | The x values that are already known. If this parameter is omitted it defaults to an array of values from 1 to the number of known ys. | ||||
new_xs | The new x values for which y values are required. If this parameter is omitted it defaults to the known xs. | ||||
const | Specifies whether the line must pass through the origin. The possible values are: | ||||
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If this parameter is omitted it defaults to TRUE. |
Returns the mean of a set of numbers with the extreme values removed.
array | An array or reference to cells containing the numbers. |
percent | The percentage of the numbers to exclude from the calculation. |
TTEST(array1, array2, tails, type)
Returns the probability result of the Student's T test.
array1 | The first range to be compared. | ||||||
array2 | The second range to be compared. | ||||||
tails | Specifies the tails to include in the distribution. Should be 1 or 2. | ||||||
type | Specifies which type of test is required. The possible values are: | ||||||
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Returns the variance (based on a population sample) of a set of numbers.
number1, ... | The numbers of which you want the variance. |
Returns the variance (based on a population sample) of a set of values.
value1, ... | The values of which you want the variance. |
Returns the variance (based on the entire population) of a set of numbers.
number1, ... | The numbers of which you want the variance. |
Returns the variance (based on the entire population) of a set of values.
value1, ... | The values of which you want the variance. |
WEIBULL(x, alpha, beta, cumulative)
Returns the Weibull distribution probability.
x | The value at which you want to evaluate the function. | ||||
alpha | The alpha value. | ||||
beta | The beta value. | ||||
cumulative | Specifies whether to return the cumulative probability or not. The possible values are: | ||||
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Returns the probability result of the z test.
array | An array or reference to cells containing the data against which x is to be tested. |
x | The value to be tested. |
sigma | The population standard deviation. If this parameter is omitted it defaults to the sample standard deviation of the data. |