# 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(DataY; DataX)

DataY is the dependent set of observations or data.

DataX 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(Value1; Value2; ...; Value30)

Value1; Value2, ..., Value30 are 1 to 30 values or ranges representing the values to be counted.

#### 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(Value1; Value2; ...; Value30)

Value1; Value2, ..., Value30 are 1 to 30 arguments representing the values to be counted.

#### 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.

## 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.

რაოდენობა არის განმეორებათა რაოდენობა.

SP არის ცდის წარმატების ალბათობა.

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.

რაოდენობა არის განმეორებათა რაოდენობა.

SP არის ცდის წარმატების ალბათობა.

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

#### Example

=BINOM.DIST(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.

=BINOM.DIST(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

რიცხვი არის მნიშვნელობა რომლისთვისაც გამა განაწილება უნდა გამოითვალოს.

თავისუფლების_ხარისხი ექსპერიმენტის თავისუფლების ხარისხი.

## BETAINV

Returns the inverse of the cumulative beta probability density function.

#### Syntax

BETAINV(რიცხვი;ალფა;ბეტა;გაშვება;დასასრული)

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

ალფა განაწილების პარამეტრი.

ბეტა განაწილების პარამეტრი.

გაშვება (არასავალდებულო) რიცხვის ქვედა ზღვარი.

დასასრული (არასავალდებულო) რიცხვის ზედა ზღვარი.

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

BETAINV(რიცხვი;ალფა;ბეტა;გაშვება;დასასრული)

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

ალფა განაწილების პარამეტრი.

ბეტა განაწილების პარამეტრი.

გაშვება (არასავალდებულო) რიცხვის ქვედა ზღვარი.

დასასრული (არასავალდებულო) რიცხვის ზედა ზღვარი.

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

=BETA.INV(0.5;5;10) returns the value 0.3257511553.

## CHIINV

Returns the inverse of the left-tailed probability of the chi-square distribution.

This function is available since LibreOffice 4.2

#### Syntax

CHISQ.INV(Probability; DegreesFreedom)

რიცხვი არის მნიშვნელობა რომლისთვისაც გამა განაწილება უნდა გამოითვალოს.

თავისუფლების_ხარისხი ექსპერიმენტის თავისუფლების ხარისხი.

#### Example

=CHISQ.INV(0,5;1) returns 0.4549364231.

## CHIINV

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

#### Syntax

CHIINV(რიცხვი; თავისუფლების ხარისხი)

რიცხვი შეცდომის ალბათონის მნიშვნელობა.

თავისუფლების_ხარისხი ექსპერიმენტის თავისუფლების ხარისხი.

#### 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(რიცხვი; თავისუფლების ხარისხი)

რიცხვი შეცდომის ალბათონის მნიშვნელობა.

თავისუფლების_ხარისხი ექსპერიმენტის თავისუფლების ხარისხი.

#### 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.

=CHISQ.INV.RT(0.05;5) returns 11.0704976935.

=CHISQ.INV.RT(0.02;5) returns 13.388222599.

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 cells that meet with certain criteria within a cell range.

#### Syntax

COUNTIF(დიაპაზონი; კრიტერიუმი)

დიაპაზონი არის დიაპაზონი რომლისთვისაც კრიტერიუმი უნდა გააქტიურდეს.

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 ".[0]" or ".\0" or "(?i).0".

#### Example

A1:A10 is a cell range containing the numbers 2000 to 2009. Cell B1 contains the number 2006. In cell B2, you enter a formula:

=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 count only negative numbers: =COUNTIF(A1:A10;"<0")

## COUNTBLANK

Returns the number of empty cells.

#### Syntax

COUNTBLANK(დიაპაზონი)

Returns the number of empty cells in the cell range Range.

#### Example

=COUNTBLANK(A1:B2) returns 4 if cells A1, A2, B1, and B2 are all empty.

## 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(რიცხვები; თავისუფლების_გრადუსები; რეჟიმი)

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

თავისუფლების_ხარისხი არის ექსპერიმენტის თავისუფლების ხარისხი.

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.

## CHIDIST

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

The probability determined by CHISQ.TEST can also be determined with CHISQ.DIST, 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(მონაცემი_B; მონაცემი_E)

მონაცემი_B დაკვირვების მასივი.

მონაცემი_E მოსალოდნელი მნიშვნელობების დიაპაზონი.

#### Example

 მონაცემი_B (დაკვირვებული) მონაცემი_E (დაკვირვებული) 1 195 170 2 151 170 3 148 170 4 189 170 5 183 170 6 154 170

=CHISQ.TEST(A1:A6;B1:B6) equals 0.0209708029. This is the probability which suffices the observed data of the theoretical Chi-square distribution.

## 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(მონაცემი_B; მონაცემი_E)

მონაცემი_B დაკვირვების მასივი.

მონაცემი_E მოსალოდნელი მნიშვნელობების დიაპაზონი.

#### Example

 მონაცემი_B (დაკვირვებული) მონაცემი_E (დაკვირვებული) 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 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 (რიცხვი; თავისუფლების ხარისხი)

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

თავისუფლების_ხარისხი არის ექსპერიმენტის თავისუფლების ხარისხი.

#### 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. CHISQ.DIST.RT 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 CHISQ.DIST.RT can also be determined by CHITEST.

This function is available since LibreOffice 4.2

#### Syntax

CHIDIST (რიცხვი; თავისუფლების ხარისხი)

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

თავისუფლების_ხარისხი არის ექსპერიმენტის თავისუფლების ხარისხი.

#### Example

=CHISQ.DIST.RT(13.27; 5) equals 0.0209757694.

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)

თვლა_1 ობიექტების სრული რაოდენობა.

SP არის ცდის წარმატების ალბათობა.

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(მონაცემი_Y; მონაცემი_X)

მონაცემი_Y მასივი ან მონაცემთა დიაპაზონი.

მონაცემი_X მასივი ან მონაცემთა დიაპაზონი.

#### Example

=RSQ(A1:A20;B1:B20) calculates the determination 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

TDIST(რიცხვები; თავისუფლების_გრადუსები; რეჟიმი)

რიცხვი არის მნიშვნელობა, რომლისთვისაც F განაწილება გამოითვლება.

თავისუფლების_ხარისხი ექსპერიმენტის თავისუფლების ხარისხი.

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

აბრუნებს t-განაწილებას.

#### Syntax

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

ალფა განაწილების პარამეტრი.

ბეტა განაწილების პარამეტრი.

გაშვება (არასავალდებულო) რიცხვის ქვედა ზღვარი.

დასასრული (არასავალდებულო) რიცხვის ზედა ზღვარი.

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

აბრუნებს t-განაწილებას.

This function is available since LibreOffice 4.2

#### Syntax

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

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

ალფა განაწილების პარამეტრი.

ბეტა განაწილების პარამეტრი.

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.

გაშვება (არასავალდებულო) რიცხვის ქვედა ზღვარი.

დასასრული (არასავალდებულო) რიცხვის ზედა ზღვარი.

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

=BETA.DIST(2;8;10;1;1;3) returns the value 0.6854706

=BETA.DIST(2;8;10;0;1;3) returns the value 1.4837646

## B

აბრუნებს ბინომინალური განაწილებით შერჩევების ალბათობას.

#### Syntax

B(Trials; SP; T1; T2)

რაოდენობა არის განმეორებათა რაოდენობა.

SP არის ცდის წარმატების ალბათობა.

T1 defines the lower limit for the number of trials.

T2 (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%.

## EXPONDIST

აბრუნებს საჩვენებელ განაწილებას.

#### Syntax

EXPONDIST(რიცხვი; ლამბდა; C)

რიცხვი ფუნქციის მნიშვნელობა.

ლამბდა არის პარამეტრის მნიშვნელობა.

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

აბრუნებს საჩვენებელ განაწილებას.

This function is available since LibreOffice 4.2

#### Syntax

EXPONDIST(რიცხვი; ლამბდა; C)

რიცხვი ფუნქციის მნიშვნელობა.

ლამბდა არის პარამეტრის მნიშვნელობა.

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

=EXPON.DIST(3;0.5;1) returns 0.7768698399.