# Statistical Functions Part One

Returns the count of cells that meet criteria in multiple ranges.

## INTERCEPT

Calculates the point at which a line will intersect the y-values by using known x-values and y-values.

#### Syntax

INTERCEPT(data_Y; data_X)

Data_Y is the dependent set of observations or data.

Data_X is the independent set of observations or data.

Names, arrays or references containing numbers must be used here. Numbers can also be entered directly.

#### Example

To calculate the intercept, use cells D3:D9 as the y value and C3:C9 as the x value from the example spreadsheet. Input will be as follows:

INTERCEPT(D3:D9;C3:C9) = 2.15.

## COUNT

Counts how many numbers are in the list of arguments. Text entries are ignored.

#### Syntax

COUNT(Number 1 [; Number 2 [; … [; Number 255]]])

Number 1, Number 2, … , Number 255 are numbers, references to cells or to cell ranges of numbers.

#### Example

The entries 2, 4, 6 and eight in the value 1 - 4 fields are to be counted.

COUNT(2;4;6;"eight") = 3. The count of numbers is therefore 3.

## COUNTA

Counts how many values are in the list of arguments. Text entries are also counted, even when they contain an empty string of length 0. If an argument is an array or reference, empty cells within the array or reference are ignored.

#### Syntax

COUNTA(Number 1 [; Number 2 [; … [; Number 255]]])

Number 1, Number 2, … , Number 255 are numbers, references to cells or to cell ranges of numbers.

#### Example

The entries 2, 4, 6 and eight in the value 1 - 4 fields are to be counted.

COUNTA(2;4;6;"eight") = 4. The count of values is therefore 4.

Returns the cumulative beta probability density function.

#### Syntax

BETADIST(Number; Alpha; Beta [; Start [; End [; Cumulative]]])

Number is the value between Start and End at which to evaluate the function.

Alpha is a parameter to the distribution.

Beta is a parameter to the distribution.

Start (optional) is the lower bound for number.

End (optional) is the upper bound for number.

Cumulative (optional) can be 0 or False to calculate the probability density function. It can be any other value or True or omitted to calculate the cumulative distribution function.

In the LibreOffice Calc functions, parameters marked as "optional" can be left out only when no parameter follows. For example, in a function with four parameters, where the last two parameters are marked as "optional", you can leave out parameter 4 or parameters 3 and 4, but you cannot leave out parameter 3 alone.

#### Example

Returns the cumulative beta probability density function. This function is available since LibreOffice 4.2.

#### Syntax

BETA.DIST(Number; Alpha; Beta; Cumulative [; Start [; End]])

Number is the value between Start and End at which to evaluate the function.

Alpha is a parameter to the distribution.

Beta is a parameter to the distribution.

Cumulative (required) can be 0 or False to calculate the probability density function. It can be any other value or True to calculate the cumulative distribution function.

Start (optional) is the lower bound for number.

End (optional) is the upper bound for number.

In the LibreOffice Calc functions, parameters marked as "optional" can be left out only when no parameter follows. For example, in a function with four parameters, where the last two parameters are marked as "optional", you can leave out parameter 4 or parameters 3 and 4, but you cannot leave out parameter 3 alone.

#### Example

=BETADIST(0.75; 3; 4) returns the value 0.96

=BETADIST(0.75; 3; 4) returns the value 0.96

## EXPONDIST

Returns the exponential distribution.

#### Syntax

EXPONDIST(Number; lambda; C)

Number is the value of the function.

Lambda is the parameter value.

C is a logical value that determines the form of the function. C = 0 calculates the density function, and C = 1 calculates the distribution.

#### Example

=EXPONDIST(3; 0.5; 1) returns 0.78.

## EXPONDIST

Returns the exponential distribution. This function is available since LibreOffice 4.2.

#### Syntax

EXPONDIST(Number; lambda; C)

Number is the value of the function.

Lambda is the parameter value.

C is a logical value that determines the form of the function. C = 0 calculates the density function, and C = 1 calculates the distribution.

#### Example

=EXPONDIST(3; 0.5; 1) returns 0.78.

## BINOMDIST

Returns the individual term binomial distribution probability.

#### Syntax

BINOMDIST(X;trials;SP;C)

X is the number of successes in a set of trials.

Trials is the number of independent trials.

SP is the probability of success on each trial.

C = 0 calculates the probability of a single event and C = 1 calculates the cumulative probability.

#### Example

=BINOMDIST(A1; 12; 0.5; 0) shows (if the values 0 to 12 are entered in A1) the probabilities for 12 flips of a coin that Heads will come up exactly the number of times entered in A1.

=BINOMDIST(A1; 12; 0.5; 1) shows the cumulative probabilities for the same series. For example, if A1 = 4, the cumulative probability of the series is 0, 1, 2, 3 or 4 times Heads (non-exclusive OR).

## BINOMDIST

Returns the individual term binomial distribution probability. This function is available since LibreOffice 4.2.

#### Syntax

BINOMDIST(X;trials;SP;C)

X is the number of successes in a set of trials.

Trials is the number of independent trials.

SP is the probability of success on each trial.

C = 0 calculates the probability of a single event and C = 1 calculates the cumulative probability.

#### Example

=BINOMDIST(A1; 12; 0.5; 0) shows (if the values 0 to 12 are entered in A1) the probabilities for 12 flips of a coin that Heads will come up exactly the number of times entered in A1.

=BINOMDIST(A1; 12; 0.5; 1) shows the cumulative probabilities for the same series. For example, if A1 = 4, the cumulative probability of the series is 0, 1, 2, 3 or 4 times Heads (non-exclusive OR).

## CHIINV

Returns the inverse of CHISQDIST.

#### Syntax

CHISQINV(Probability; Degrees of Freedom)

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

Degrees_freedom is the degrees of freedom of the experiment.

## BETAINV

Returns the inverse of the cumulative beta probability density function.

#### Syntax

BETAINV(Number; Alpha; Beta [; Start [; End]])

Number is the value between Start and End at which to evaluate the function.

Alpha is a parameter to the distribution.

Beta is a parameter to the distribution.

Start (optional) is the lower bound for number.

End (optional) is the upper bound for number.

In the LibreOffice Calc functions, parameters marked as "optional" can be left out only when no parameter follows. For example, in a function with four parameters, where the last two parameters are marked as "optional", you can leave out parameter 4 or parameters 3 and 4, but you cannot leave out parameter 3 alone.

#### Example

=BETAINV(0.5; 5; 10) returns the value 0.33.

## BETAINV

Returns the inverse of the cumulative beta probability density function. This function is available since LibreOffice 4.2.

#### Syntax

BETA.INV(Number; Alpha; Beta [; Start [; End]])

Number is the value between Start and End at which to evaluate the function.

Alpha is a parameter to the distribution.

Beta is a parameter to the distribution.

Start (optional) is the lower bound for number.

End (optional) is the upper bound for number.

In the LibreOffice Calc functions, parameters marked as "optional" can be left out only when no parameter follows. For example, in a function with four parameters, where the last two parameters are marked as "optional", you can leave out parameter 4 or parameters 3 and 4, but you cannot leave out parameter 3 alone.

#### Example

=BETAINV(0.5; 5; 10) returns the value 0.33.

## CHIINV

Returns the inverse of the one-tailed probability of the chi-squared distribution. This function is available since LibreOffice 4.2.

#### Syntax

CHISQ.INV(Probability; DegreesFreedom)

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

Degrees_freedom is the degrees of freedom of the experiment.

#### Example

=CHIINV(0.05; 5) returns 11.07.

## CHIINV

Returns the inverse of the one-tailed probability of the chi-squared distribution.

#### Syntax

CHIINV(number; degrees_freedom)

Number is the value of the error probability.

Degrees_freedom is the degrees of freedom of the experiment.

#### Example

A die is thrown 1020 times. The numbers on the die 1 through 6 come up 195, 151, 148, 189, 183 and 154 times (observation values). The hypothesis that the die is not fixed is to be tested.

The Chi square distribution of the random sample is determined by the formula given above. Since the expected value for a given number on the die for n throws is n times 1/6, thus 1020/6 = 170, the formula returns a Chi square value of 13.27.

If the (observed) Chi square is greater than or equal to the (theoretical) Chi square CHIINV, the hypothesis will be discarded, since the deviation between theory and experiment is too great. If the observed Chi square is less that CHIINV, the hypothesis is confirmed with the indicated probability of error.

=CHIINV(0.05; 5) returns 11.07.

=CHIINV(0.02; 5) returns 13.39.

If the probability of error is 5%, the die is not true. If the probability of error is 2%, there is no reason to believe it is fixed.

## CHIINV

Returns the inverse of the one-tailed probability of the chi-squared distribution. This function is available since LibreOffice 4.2.

#### Syntax

CHIINV(number; degrees_freedom)

Number is the value of the error probability.

Degrees_freedom is the degrees of freedom of the experiment.

#### Example

A die is thrown 1020 times. The numbers on the die 1 through 6 come up 195, 151, 148, 189, 183 and 154 times (observation values). The hypothesis that the die is not fixed is to be tested.

The Chi square distribution of the random sample is determined by the formula given above. Since the expected value for a given number on the die for n throws is n times 1/6, thus 1020/6 = 170, the formula returns a Chi square value of 13.27.

If the (observed) Chi square is greater than or equal to the (theoretical) Chi square CHIINV, the hypothesis will be discarded, since the deviation between theory and experiment is too great. If the observed Chi square is less that CHIINV, the hypothesis is confirmed with the indicated probability of error.

=CHIINV(0.05; 5) returns 11.07.

=CHIINV(0.02; 5) returns 13.39.

If the probability of error is 5%, the die is not true. If the probability of error is 2%, there is no reason to believe it is fixed.

## COUNTIF

Returns the number of elements that meet with certain criteria within a cell range.

#### Syntax

COUNTIF(range; criteria)

Range is the range to which the criteria are to be applied.

Criteria indicates the criteria in the form of a number, an expression or a character string. These criteria determine which cells are counted.

The search supports wildcards or regular expressions. With regular expressions enabled, you can enter "all.*", for example to find the first location of "all" followed by any characters. If you want to search for a text that is also a regular expression, you must either precede every character with a "\" character, or enclose the text into \Q...\E. You can switch the automatic evaluation of wildcards or regular expression on and off in - LibreOffice Calc - Calculate. When using functions where one or more arguments are search criteria strings that represents a regular expression, the first attempt is to convert the string criteria to numbers. For example, ".0" will convert to 0.0 and so on. If successful, the match will not be a regular expression match but a numeric match. However, when switching to a locale where the decimal separator is not the dot makes the regular expression conversion work. To force the evaluation of the regular expression instead of a numeric expression, use some expression that can not be misread as numeric, such as "." or ".\0" or "(?i).0".

#### Example

An example can be found under SUM().

=COUNTIF(A1:A10;2006) - this returns 1.

=COUNTIF(A1:A10;B1) - this returns 1.

=COUNTIF(A1:A10;">=2006") - this returns 4.

=COUNTIF(A1:A10;"<"&B1) - when B1 contains 2006, this returns 6.

=COUNTIF(A1:A10;C2) where cell C2 contains the text >2006 counts the number of cells in the range A1:A10 which are >2006.

To sum up only negative numbers: SUMIF(A1:A10;"<0")

## CHIDIST

Returns the probability density function or the cumulative distribution function for the chi-square distribution. This function is available since LibreOffice 4.2.

#### Syntax

TDIST(Number; Degrees_freedom; Mode)

Number is the chi-square value of the random sample used to determine the error probability.

Degrees_freedom are the degrees of freedom of the experiment.

Cumulative can be 0 or False to calculate the probability density function. It can be any other value or True to calculate the cumulative distribution function.

#### Example

=CHISQ.DIST(3; 2; 0) equals 0.1115650801, the probability density function with 2 degrees of freedom, at x = 3.

=CHISQ.DIST(3; 2; 1) equals 0.7768698399, the cumulative chi-square distribution with 2 degrees of freedom, at the value x = 3.

## CHITEST

Returns the probability of a deviance from a random distribution of two test series based on the chi-squared test for independence. CHITEST returns the chi-squared distribution of the data.

The probability determined by CHITEST can also be determined with CHIDIST, in which case the Chi square of the random sample must then be passed as a parameter instead of the data row.

#### Syntax

CHITEST(Data_B; Data_E)

Data_B is the array of the observations.

Data_E is the range of the expected values.

#### Example

 Data_B (observed) Data_E (expected) 1 195 170 2 151 170 3 148 170 4 189 170 5 183 170 6 154 170

=CHITEST(A1:A6; B1:B6) equals 0.02. This is the probability which suffices the observed data of the theoretical Chi-square distribution.

## CHIDIST

Returns the probability of a deviance from a random distribution of two test series based on the chi-squared test for independence. CHITEST returns the chi-squared distribution of the data.

The probability determined by CHITEST can also be determined with CHIDIST, in which case the Chi square of the random sample must then be passed as a parameter instead of the data row. This function is available since LibreOffice 4.2.

#### Syntax

CHITEST(Data_B; Data_E)

Data_B is the array of the observations.

Data_E is the range of the expected values.

#### Example

 Data_B (observed) Data_E (expected) 1 195 170 2 151 170 3 148 170 4 189 170 5 183 170 6 154 170

=CHITEST(A1:A6; B1:B6) equals 0.02. This is the probability which suffices the observed data of the theoretical Chi-square distribution.

## B

Returns the probability of a sample with binomial distribution.

#### Syntax

B(Trials; SP; T1 [; T2])

Trials is the number of independent trials.

SP is the probability of success on each trial.

T_1 defines the lower limit for the number of trials.

T_2 (optional) defines the upper limit for the number of trials.

#### Example

What is the probability with ten throws of the dice, that a six will come up exactly twice? The probability of a six (or any other number) is 1/6. The following formula combines these factors:

=B(10; 1/6; 2) returns a probability of 29%.

## CHIDIST

Returns the probability value from the indicated Chi square that a hypothesis is confirmed. CHIDIST compares the Chi square value to be given for a random sample that is calculated from the sum of (observed value-expected value)^2/expected value for all values with the theoretical Chi square distribution and determines from this the probability of error for the hypothesis to be tested.

The probability determined by CHIDIST can also be determined by CHITEST.

#### Syntax

CHIDIST (Number; degrees_freedom)

Number is the chi-square value of the random sample used to determine the error probability.

Degrees_freedom are the degrees of freedom of the experiment.

#### Example

=CHIDIST(13.27; 5) equals 0.02.

If the Chi square value of the random sample is 13.27 and if the experiment has 5 degrees of freedom, then the hypothesis is assured with a probability of error of 2%.

## CHIDIST

Returns the probability value from the indicated Chi square that a hypothesis is confirmed. CHIDIST compares the Chi square value to be given for a random sample that is calculated from the sum of (observed value-expected value)^2/expected value for all values with the theoretical Chi square distribution and determines from this the probability of error for the hypothesis to be tested.

The probability determined by CHIDIST can also be determined by CHITEST. This function is available since LibreOffice 4.2.

#### Syntax

CHIDIST (Number; degrees_freedom)

Number is the chi-square value of the random sample used to determine the error probability.

Degrees_freedom are the degrees of freedom of the experiment.

#### Example

=CHIDIST(13.27; 5) equals 0.02.

If the Chi square value of the random sample is 13.27 and if the experiment has 5 degrees of freedom, then the hypothesis is assured with a probability of error of 2%.

## BINOM.INV

Returns the smallest value for which the cumulative binomial distribution is greater than or equal to a criterion value. This function is available since LibreOffice 4.2.

#### Syntax

BINOM.INV(Trials; SP; Alpha)

Trials is the total number of trials.

SP is the probability of success on each trial.

Alpha The border probability that is attained or exceeded.

#### Example

=BINOM.INV(8;0.6;0.9) returns 7, the smallest value for which the cumulative binomial distribution is greater than or equal to a criterion value.

## RSQ

Returns the square of the Pearson correlation coefficient based on the given values. RSQ (also called determination coefficient) is a measure for the accuracy of an adjustment and can be used to produce a regression analysis.

#### Syntax

RSQ(Data_Y; Data_X)

Data_Y is an array or range of data points.

Data_X is an array or range of data points.

#### Example

=RSQ(A1:A20; B1:B20) calculates the correlation coefficient for both data sets in columns A and B.

## CHIDIST

Returns the value of the probability density function or the cumulative distribution function for the chi-square distribution.

#### Syntax

CHISQDIST(Number; Degrees Of Freedom [; Cumulative])

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

Degrees_freedom is the degrees of freedom of the experiment.

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

## COUNTBLANK

Враќа број на празни ќелии.

#### Syntax

COUNTBLANK(range)

range is the cell range in which the empty cells are counted.

#### Example

Entering = COUNTBLANK (A1:C3) in an empty cell range results in 9.