LibreOffice 7.1 Help

Returns the (1-alpha) confidence interval for a normal distribution.

CONFIDENCE(Alpha; STDEV; Size)

Alpha is the level of the confidence interval.

STDEV is the standard deviation for the total population.

Size is the size of the total population.

=CONFIDENCE.T(0.05;1.5;100) gives 0.2976325427.

Returns the (1-alpha) confidence interval for a normal distribution.

CONFIDENCE(Alpha; STDEV; Size)

Alpha is the level of the confidence interval.

STDEV is the standard deviation for the total population.

Size is the size of the total population.

=CONFIDENCE.NORM(0.05;1.5;100) gives 0.2939945977.

Returns the (1-alpha) confidence interval for a normal distribution.

CONFIDENCE(Alpha; STDEV; Size)

Alpha is the level of the confidence interval.

STDEV is the standard deviation for the total population.

Size is the size of the total population.

=CONFIDENCE(0.05;1.5;100) gives 0.29.

Returns the Rank_c-th largest value in a data set.

LARGE(Data; Rank_c)

Data is the cell range of data.

RankC is the ranking of the value. If RankC is an array, the function becomes an array function.

=LARGE(A1:C50;2) gives the second largest value in A1:C50.

=LARGE(A1:C50;B1:B5) entered as an array function gives an array of the c-th largest value in A1:C50 with ranks defined in B1:B5.

Returns the Rank_c-th smallest value in a data set.

SMALL(Data; Rank_c)

Data is the cell range of data.

RankC is the rank of the value. If RankC is an array, the function becomes an array function.

=SMALL(A1:C50;2) gives the second smallest value in A1:C50.

=SMALL(A1:C50;B1:B5) entered as an array function gives an array of the c-th smallest value in A1:C50 with ranks defined in B1:B5.

Returns the correlation coefficient between two data sets.

CORREL(Data_1; Data_2)

Data_1 is the first record array.

Data_2 is the second record array.

=CORREL(A1:A50; B1:B50) calculates the correlation coefficient as a measure of the linear correlation of the two data sets.

Returns the covariance of the product of paired deviations, for a sample of the population.

COVARIANCE.S(Data1; Data2)

Data_1 is the first record array.

Data_2 is the second record array.

=COVARIANCE.S(A1:A30;B1:B30)

Returns the covariance of the product of paired deviations, for the entire population.

COVARIANCE.P(Data1; Data2)

Data_1 is the first record array.

Data_2 is the second record array.

=COVARIANCE.P(A1:A30;B1:B30)

Returns the covariance of the product of paired deviations.

COVAR(Data_1; Data_2)

Data_1 is the first record array.

Data_2 is the second record array.

=COVAR(A1:A30;B1:B30)

Returns the inverse of the lognormal distribution.

LOGINV(Number [; Mean [; StDev]])

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

Mean is the arithmetic mean of the standard logarithmic distribution.

Mean is the mean value of the standard logarithmic distribution.

=LOGINV(0.05;0;1) returns 0.1930408167.

Returns the inverse of the lognormal distribution.

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

NORMINV(Number; Mean; STDEV)

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

Mean is the arithmetic mean of the standard logarithmic distribution.

Mean is the mean value of the standard logarithmic distribution.

=LOGNORM.INV(0.05;0;1) returns 0.1930408167.

Returns the kurtosis of a data set (at least 4 values required).

KURT(Number 1 [; Number 2 [; â€¦ [; Number 255]]])

The parameters should specify at least four values.

=KURT(A1;A2;A3;A4;A5;A6)

Returns the smallest value for which the cumulative binomial distribution is greater than or equal to a criterion value.

CRITBINOM(Trials; SP; Alpha)

Trials is the total number of trials.

SP is the probability of success for one trial.

Alpha is the threshold probability to be reached or exceeded.

=CRITBINOM(100;0.5;0.1) yields 44.

Returns the values of a Gamma distribution.

LOGNORMDIST(Number [; Mean [; StDev [; Cumulative]]])

Number is the probability value for which the standard logarithmic distribution is to be calculated.

Mean is the mean value of the standard logarithmic distribution.

Mean is the mean value of the standard logarithmic distribution.

C = 0 calculates the density function C = 1 the distribution.

=LOGNORMDIST(0.1;0;1) returns 0.01.

Returns the values of a Gamma distribution.

LOGNORM.DIST(Number; Mean; StDev; Cumulative)

Number is the probability value for which the standard logarithmic distribution is to be calculated.

Mean is the mean value of the standard logarithmic distribution.

Mean is the mean value of the standard logarithmic distribution.

C = 0 calculates the density function C = 1 the distribution.

=LOGNORM.DIST(0.1;0;1;1) returns 0.0106510993.