LibreOffice 25.2 Help
Returns the count of cells that meet criteria in multiple ranges.
აბრუნებს ბინომინალური განაწილებით შერჩევების ალბათობას.
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.
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%.
აბრუნებს t-განაწილებას.
BETADIST(Number; Alpha; Beta [; Start [; End [; Cumulative]]])
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.
=BETADIST(0.75;3;4) returns the value 0.96.
აბრუნებს t-განაწილებას.
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.
=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
COM.MICROSOFT.BETA.DIST
Returns the inverse of the cumulative Beta probability density function.
BETAINV(Number; Alpha; Beta [; Start [; End]])
Number is the probability associated with the Beta distribution for the given arguments Alpha and Beta.
Alpha is a strictly positive parameter of the Beta distribution.
Beta is a strictly positive parameter of the Beta distribution.
Start (optional) is the lower bound of the output range of the function. If omitted, the default value is 0.
End (optional) is the upper bound of the output range of the function. If omitted, the default value is 1.
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.
=BETAINV(0.5;5;10) returns the value 0.3257511553.
Returns the inverse of the cumulative Beta probability density function.
BETA.INV(Number; Alpha; Beta [; Start [; End]])
Number is the probability associated with the Beta distribution for the given arguments Alpha and Beta.
Alpha is a strictly positive parameter of the Beta distribution.
Beta is a strictly positive parameter of the Beta distribution.
Start (optional) is the lower bound of the output range of the function. If omitted, the default value is 0.
End (optional) is the upper bound of the output range of the function. If omitted, the default value is 1.
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.
=BETA.INV(0.5;5;10) returns the value 0.3257511553.
COM.MICROSOFT.BETA.INV
Returns the smallest value for which the cumulative binomial distribution is greater than or equal to a criterion value.
BINOM.INV(Trials; SP; Alpha)
თვლა_1 ობიექტების სრული რაოდენობა.
SP არის ცდის წარმატების ალბათობა.
Alpha The border probability that is attained or exceeded.
=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.
COM.MICROSOFT.BINOM.INV
Returns the individual term binomial distribution probability.
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.
=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).
Returns the individual term binomial distribution probability.
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.
=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).
COM.MICROSOFT.BINOM.DIST
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.
CHITEST(მონაცემი_B; მონაცემი_E)
მონაცემი_B დაკვირვების მასივი.
მონაცემი_E მოსალოდნელი მნიშვნელობების დიაპაზონი.
| 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.
COM.MICROSOFT.CHISQ.TEST
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.
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.
=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%.
Returns the probability density function or the cumulative distribution function for the chi-square distribution.
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.
=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.
COM.MICROSOFT.CHISQ.DIST
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.
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.
=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%.
COM.MICROSOFT.CHISQ.DIST.RT
Returns the value of the probability density function or the cumulative distribution function for the chi-square distribution.
CHISQDIST(Number; Degrees Of Freedom [; Cumulative])
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.
Returns the inverse of CHISQDIST.
CHISQINV(Probability; Degrees of Freedom)
რიცხვი არის მნიშვნელობა რომლისთვისაც გამა განაწილება უნდა გამოითვალოს.
თავისუფლების_ხარისხი ექსპერიმენტის თავისუფლების ხარისხი.
Returns the inverse of the left-tailed probability of the chi-square distribution.
CHISQ.INV(Probability; DegreesFreedom)
რიცხვი არის მნიშვნელობა რომლისთვისაც გამა განაწილება უნდა გამოითვალოს.
თავისუფლების_ხარისხი ექსპერიმენტის თავისუფლების ხარისხი.
=CHISQ.INV(0,5;1) returns 0.4549364231.
COM.MICROSOFT.CHISQ.INV
Returns the inverse of the one-tailed probability of the chi-squared distribution.
CHIINV(რიცხვი; თავისუფლების ხარისხი)
რიცხვი შეცდომის ალბათონის მნიშვნელობა.
თავისუფლების_ხარისხი ექსპერიმენტის თავისუფლების ხარისხი.
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.
Returns the inverse of the one-tailed probability of the chi-squared distribution.
CHIINV(რიცხვი; თავისუფლების ხარისხი)
რიცხვი შეცდომის ალბათონის მნიშვნელობა.
თავისუფლების_ხარისხი ექსპერიმენტის თავისუფლების ხარისხი.
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.
COM.MICROSOFT.CHISQ.INV.RT
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.
CHITEST(მონაცემი_B; მონაცემი_E)
მონაცემი_B დაკვირვების მასივი.
მონაცემი_E მოსალოდნელი მნიშვნელობების დიაპაზონი.
=CHITEST(A1:A6;B1:B6) equals 0.02. This is the probability which suffices the observed data of the theoretical Chi-square distribution.
Counts how many numbers are in the list of arguments. Text entries are ignored.
COUNT(Number 1 [; Number 2 [; … [; Number 255]]])
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.
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.
COUNTA(Number 1 [; Number 2 [; … [; Number 255]]])
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 number of empty cells.
COUNTBLANK(დიაპაზონი)
Returns the number of empty cells in the cell range Range.
=COUNTBLANK(A1:B2) returns 4 if cells A1, A2, B1, and B2 are all empty.
Returns the number of cells that meet with certain criteria within a cell range.
COUNTIF(Range; Criterion)
დიაპაზონი არის დიაპაზონი რომლისთვისაც კრიტერიუმი უნდა გააქტიურდეს.
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")
აბრუნებს საჩვენებელ განაწილებას.
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.
=EXPONDIST(3;0.5;1) returns 0.78.
აბრუნებს საჩვენებელ განაწილებას.
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.
=EXPON.DIST(3;0.5;1) returns 0.7768698399.
COM.MICROSOFT.EXPON.DIST
Calculates the point at which a line will intersect the y-values by using known x-values and y-values.
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.
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.
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.
RSQ(მონაცემი_Y; მონაცემი_X)
მონაცემი_Y მასივი ან მონაცემთა დიაპაზონი.
მონაცემი_X მასივი ან მონაცემთა დიაპაზონი.
=RSQ(A1:A20;B1:B20) calculates the determination coefficient for both data sets in columns A and B.