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# Statistical Functions Part Two

## F.DIST

Calculates the values of the left tail of the F distribution.

### தொடரமைப்பு

F.DIST(Number; DegreesFreedom1; DegreesFreedom2; Cumulative)

Number is the value for which the F distribution is to be calculated.

degreesFreedom1 is the degrees of freedom in the numerator in the F distribution.

degreesFreedom2 is the degrees of freedom in the denominator in the F distribution.

Cumulative = 0 or False calculates the density function Cumulative = 1 or True calculates the distribution.

### எடுத்துக்காட்டு

=F.DIST(0.8;8;12;0) yields 0.7095282499.

=F.DIST(0.8;8;12;1) yields 0.3856603563.

## F.DIST.RT

Calculates the values of the right tail of the F distribution.

### தொடரமைப்பு

F.DIST.RT(Number; DegreesFreedom1; DegreesFreedom2)

Number is the value for which the F distribution is to be calculated.

degreesFreedom1 is the degrees of freedom in the numerator in the F distribution.

degreesFreedom2 is the degrees of freedom in the denominator in the F distribution.

### எடுத்துக்காட்டு

=F.DIST.RT(0.8;8;12) yields 0.6143396437.

## F.INV

Returns the inverse of the cumulative F distribution. The F distribution is used for F tests in order to set the relation between two differing data sets.

### தொடரமைப்பு

F.INV(Number; DegreesFreedom1; DegreesFreedom2)

Number is probability value for which the inverse F distribution is to be calculated.

DegreesFreedom1 is the number of degrees of freedom in the numerator of the F distribution.

DegreesFreedom2 is the number of degrees of freedom in the denominator of the F distribution.

### எடுத்துக்காட்டு

=F.INV(0.5;5;10) yields 0.9319331609.

## F.INV.RT

Returns the inverse right tail of the F distribution.

### தொடரமைப்பு

F.INV.RT(Number; DegreesFreedom1; DegreesFreedom2)

Number is probability value for which the inverse F distribution is to be calculated.

DegreesFreedom1 is the number of degrees of freedom in the numerator of the F distribution.

DegreesFreedom2 is the number of degrees of freedom in the denominator of the F distribution.

### எடுத்துக்காட்டு

=F.INV.RT(0.5;5;10) yields 0.9319331609.

## F.TEST

Returns the result of an F test.

### தொடரமைப்பு

F.TEST(Data1; Data2)

Data1 is the first record array.

Data2 is the second record array.

### எடுத்துக்காட்டு

=F.TEST(A1:A30;B1:B12) calculates whether the two data sets are different in their variance and returns the probability that both sets could have come from the same total population.

## FDIST

Calculates the values of an F distribution.

### தொடரமைப்பு

FDIST(Number; DegreesFreedom1; DegreesFreedom2)

Number is the value for which the F distribution is to be calculated.

degreesFreedom1 is the degrees of freedom in the numerator in the F distribution.

degreesFreedom2 is the degrees of freedom in the denominator in the F distribution.

### எடுத்துக்காட்டு

=FDIST(0.8;8;12) yields 0.61.

## FINV

Returns the inverse of the F probability distribution. The F distribution is used for F tests in order to set the relation between two differing data sets.

### தொடரமைப்பு

FINV(Number; DegreesFreedom1; DegreesFreedom2)

Number is probability value for which the inverse F distribution is to be calculated.

DegreesFreedom1 is the number of degrees of freedom in the numerator of the F distribution.

DegreesFreedom2 is the number of degrees of freedom in the denominator of the F distribution.

### எடுத்துக்காட்டு

=FINV(0.5;5;10) yields 0.93.

## FISHER

Returns the Fisher transformation for x and creates a function close to a normal distribution.

### தொடரமைப்பு

FISHER(Number)

எண் சோதனைக்குரிய எண்.

### எடுத்துக்காட்டு

=FISHER(0.5) yields 0.55.

## FISHERINV

Returns the inverse of the Fisher transformation for x and creates a function close to a normal distribution.

### தொடரமைப்பு

FISHERINV(Number)

Number is the value that is to undergo reverse-transformation.

### எடுத்துக்காட்டு

=FISHERINV(0.5) yields 0.46.

## FTEST

Returns the result of an F test.

### தொடரமைப்பு

FTEST(Data1; Data2)

Data1 is the first record array.

Data2 is the second record array.

### எடுத்துக்காட்டு

=FTEST(A1:A30;B1:B12) calculates whether the two data sets are different in their variance and returns the probability that both sets could have come from the same total population.

## GAMMA

Returns the Gamma function value. Note that GAMMAINV is not the inverse of GAMMA, but of GAMMADIST.

### தொடரமைப்பு

Number is the number for which the Gamma function value is to be calculated.

## GAMMA.DIST

Returns the values of a Gamma distribution.

The inverse function is GAMMAINV or GAMMA.INV.

This function is identical to GAMMADIST and was introduced for interoperability with other office suites.

### தொடரமைப்பு

GAMMA.DIST(Number; Alpha; Beta; C)

Number is the value for which the Gamma distribution is to be calculated.

Alpha is the parameter Alpha of the Gamma distribution.

Beta is the parameter Beta of the Gamma distribution.

C (optional) = 0 or False calculates the density function C = 1 or True calculates the distribution.

### எடுத்துக்காட்டு

=GAMMA.DIST(2;1;1;1) yields 0.86.

## GAMMA.INV

Returns the inverse of the Gamma cumulative distribution GAMMADIST. This function allows you to search for variables with different distribution.

This function is identical to GAMMAINV and was introduced for interoperability with other office suites.

### தொடரமைப்பு

GAMMA.INV(Number; Alpha; Beta)

Number is the probability value for which the inverse Gamma distribution is to be calculated.

Alpha is the parameter Alpha of the Gamma distribution.

Beta is the parameter Beta of the Gamma distribution.

### எடுத்துக்காட்டு

=GAMMA.INV(0.8;1;1) yields 1.61.

## GAMMADIST

Returns the values of a Gamma distribution.

The inverse function is GAMMAINV.

### தொடரமைப்பு

GAMMADIST(Number; Alpha; Beta; C)

Number is the value for which the Gamma distribution is to be calculated.

Alpha is the parameter Alpha of the Gamma distribution.

Beta is the parameter Beta of the Gamma distribution.

C (optional) = 0 or False calculates the density function C = 1 or True calculates the distribution.

### எடுத்துக்காட்டு

=GAMMADIST(2;1;1;1) yields 0.86.

## GAMMAINV

Returns the inverse of the Gamma cumulative distribution GAMMADIST. This function allows you to search for variables with different distribution.

### தொடரமைப்பு

GAMMAINV(Number; Alpha; Beta)

Number is the probability value for which the inverse Gamma distribution is to be calculated.

Alpha is the parameter Alpha of the Gamma distribution.

Beta is the parameter Beta of the Gamma distribution.

### எடுத்துக்காட்டு

=GAMMAINV(0.8;1;1) yields 1.61.

## GAMMALN

Returns the natural logarithm of the Gamma function: G(x).

### தொடரமைப்பு

GAMMALN(Number)

Number is the value for which the natural logarithm of the Gamma function is to be calculated.

### எடுத்துக்காட்டு

=GAMMALN(2) yields 0.

## GAMMALN.PRECISE

Returns the natural logarithm of the Gamma function: G(x).

### தொடரமைப்பு

GAMMALN.PRECISE(Number)

Number is the value for which the natural logarithm of the Gamma function is to be calculated.

### எடுத்துக்காட்டு

=GAMMALN.PRECISE(2) yields 0.

## GAUSS

Returns the standard normal cumulative distribution.

It is GAUSS(x)=NORMSDIST(x)-0.5

### தொடரமைப்பு

GAUSS(Number)

Number is the value for which the value of the standard normal distribution is to be calculated.

### எடுத்துக்காட்டு

=GAUSS(0.19) = 0.08

=GAUSS(0.0375) = 0.01

## GEOMEAN

Returns the geometric mean of a sample.

### தொடரமைப்பு

GEOMEAN(Number1; Number2; ...; Number30)

Number1, Number2, ..., Number30 are numeric arguments or ranges that represent a random sample.

### எடுத்துக்காட்டு

=GEOMEAN(23;46;69) = 41.79. The geometric mean value of this random sample is therefore 41.79.

## HARMEAN

Returns the harmonic mean of a data set.

### தொடரமைப்பு

HARMEAN(Number1; Number2; ...; Number30)

Number1, Number2, ..., Number30 are up to 30 values or ranges, that can be used to calculate the harmonic mean.

### எடுத்துக்காட்டு

=HARMEAN(23;46;69) = 37.64. The harmonic mean of this random sample is thus 37.64

## HYPGEOM.DIST

Returns the hypergeometric distribution.

### தொடரமைப்பு

HYPGEOM.DIST(X; NSample; Successes; NPopulation; Cumulative)

X is the number of results achieved in the random sample.

NSample is the size of the random sample.

Successes is the number of possible results in the total population.

NPopulation is the size of the total population.

Cumulative : 0 or False calculates the probability density function. Other values or True calculates the cumulative distribution function.

### எடுத்துக்காட்டுகள்

=HYPGEOM.DIST(2;2;90;100;0) yields 0.8090909091. If 90 out of 100 pieces of buttered toast fall from the table and hit the floor with the buttered side first, then if 2 pieces of buttered toast are dropped from the table, the probability is 81%, that both will strike buttered side first.

=HYPGEOM.DIST(2;2;90;100;1) yields 1.

## HYPGEOMDIST

Returns the hypergeometric distribution.

### தொடரமைப்பு

HYPGEOMDIST(X; NSample; Successes; NPopulation)

X is the number of results achieved in the random sample.

NSample is the size of the random sample.

Successes is the number of possible results in the total population.

NPopulation is the size of the total population.

### எடுத்துக்காட்டு

=HYPGEOMDIST(2;2;90;100) yields 0.81. If 90 out of 100 pieces of buttered toast fall from the table and hit the floor with the buttered side first, then if 2 pieces of buttered toast are dropped from the table, the probability is 81%, that both will strike buttered side first.

## TRIMMEAN

Returns the mean of a data set without the Alpha percent of data at the margins.

### தொடரமைப்பு

TRIMMEAN(Data; Alpha)

Data is the array of data in the sample.

Alpha is the percentage of the marginal data that will not be taken into consideration.

### எடுத்துக்காட்டு

=TRIMMEAN(A1:A50; 0.1) calculates the mean value of numbers in A1:A50, without taking into consideration the 5 percent of the values representing the highest values and the 5 percent of the values representing the lowest ones. The percentage numbers refer to the amount of the untrimmed mean value, not to the number of summands.

## Z.TEST

Calculates the probability of observing a z-statistic greater than the one computed based on a sample.

### தொடரமைப்பு

Z.TEST(Data; mu; Sigma)

Data is the given sample, drawn from a normally distributed population.

mu is the known mean of the population.

Sigma (optional) is the known standard deviation of the population. If omitted, the standard deviation of the given sample is used.

### எடுத்துக்காட்டு

=Z.TEST(A2:A20; 9; 2) returns the result of a z-test on a sample A2:A20 drawn from a population with known mean 9 and known standard deviation 2.

## ZTEST

Calculates the probability of observing a z-statistic greater than the one computed based on a sample.

### தொடரமைப்பு

ZTEST(Data; mu; Sigma)

Data is the given sample, drawn from a normally distributed population.

mu is the known mean of the population.

Sigma (optional) is the known standard deviation of the population. If omitted, the standard deviation of the given sample is used.

See also the Wiki page.

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