Statistical Functions Part Five/text/scalc/01/04060185.xhpStatistical Functions Part Five
RANK functionnumbers;determining ranksRANKReturns the rank of a number in a sample.SyntaxRANK(Value; Data; Type)Value is the value, whose rank is to be determined.Data is the array or range of data in the sample.Type (optional) is the sequence order.Type = 0 means descending from the last item of the array to the first (this is the default), Type = 1 means ascending from the first item of the range to the last.Example=RANK(A10;A1:A50) returns the ranking of the value in A10 in value range A1:A50. If Value does not exist within the range an error message is displayed.SKEW functionSKEWReturns the skewness of a distribution.SyntaxSKEW(Number1; Number2; ...Number30)Number1, Number2...Number30 are numerical values or ranges.Example=SKEW(A1:A50) calculates the value of skew for the data referenced.regression lines;FORECAST functionextrapolationsFORECAST functionmw made "regression lines" a two level entryFORECASTExtrapolates future values based on existing x and y values.SyntaxFORECAST(Value; DataY; DataX)Value is the x value, for which the y value on the linear regression is to be returned.DataY is the array or range of known y's.DataX is the array or range of known x's.Example=FORECAST(50;A1:A50;B1;B50) returns the Y value expected for the X value of 50 if the X and Y values in both references are linked by a linear trend.STDEV functionstandard deviations in statistics;based on a sampleSTDEVEstimates the standard deviation based on a sample.SyntaxSTDEV(Number1; Number2; ...Number30)Number1, Number2, ... Number30 are numerical values or ranges representing a sample based on an entire population.Example=STDEV(A1:A50) returns the estimated standard deviation based on the data referenced.STDEVA functionSTDEVACalculates the standard deviation of an estimation based on a sample.SyntaxSTDEVA(Value1;Value2;...Value30)Value1, Value2, ...Value30 are values or ranges representing a sample derived from an entire population. Text has the value 0.Example=STDEVA(A1:A50) returns the estimated standard deviation based on the data referenced.STDEVP functionstandard deviations in statistics;based on a populationSTDEVPCalculates the standard deviation based on the entire population.SyntaxSTDEVP(Number1;Number2;...Number30)Number 1,Number 2,...Number 30 are numerical values or ranges representing a sample based on an entire population.Example=STDEVP(A1:A50) returns a standard deviation of the data referenced.STDEVPA functionSTDEVPACalculates the standard deviation based on the entire population.SyntaxSTDEVPA(Value1;Value2;...Value30)Value1,value2,...value30 are values or ranges representing a sample derived from an entire population. Text has the value 0.Example=STDEVPA(A1:A50) returns the standard deviation of the data referenced.STANDARDIZE functionconverting;random variables, into normalized valuesSTANDARDIZEConverts a random variable to a normalized value.SyntaxSTANDARDIZE(Number; Mean; StDev)Number is the value to be standardized.Mean is the arithmetic mean of the distribution.StDev is the standard deviation of the distribution.Example=STANDARDIZE(11;10;1) returns 1. The value 11 in a normal distribution with a mean of 10 and a standard deviation of 1 is as much above the mean of 10, as the value 1 is above the mean of the standard normal distribution.NORMSINV functionnormal distribution;inverse of standardNORMSINVReturns the inverse of the standard normal cumulative distribution.SyntaxNORMINV(Number)Number is the probability to which the inverse standard normal distribution is calculated.Example=NORMSINV(0.908789) returns 1.3333.NORMSDIST functionnormal distribution;statisticsNORMSDISTReturns the standard normal cumulative distribution function. The distribution has a mean of zero and a standard deviation of one.It is GAUSS(x)=NORMSDIST(x)-0.5SyntaxNORMSDIST(Number)Number is the value to which the standard normal cumulative distribution is calculated.Example=NORMSDIST(1) returns 0.84. The area below the standard normal distribution curve to the left of X value 1 is 84% of the total area.SLOPE functionSLOPEReturns the slope of the linear regression line. The slope is adapted to the data points set in the y and x values.SyntaxSLOPE(DataY; DataX)DataY is the array or matrix of Y data.DataX is the array or matrix of X data.Example=SLOPE(A1:A50;B1:B50)STEYX functionstandard errors;statistical functionsmw changed "standard errors"STEYXReturns the standard error of the predicted y value for each x in the regression.SyntaxSTEYX(DataY; DataX)DataY is the array or matrix of Y data.DataX is the array or matrix of X data.Example=STEXY(A1:A50;B1:B50)DEVSQ functionsums;of squares of deviationsDEVSQReturns the sum of squares of deviations based on a sample mean.SyntaxDEVSQ(Number1; Number2; ...Number30)Number1, Number2, ...Number30 numerical values or ranges representing a sample. Example=DEVSQ(A1:A50)TINV functioninverse of t-distributionTINVReturns the inverse of the t-distribution.SyntaxTINV(Number; DegreesFreedom)Number is the probability associated with the two-tailed t-distribution.DegreesFreedom is the number of degrees of freedom for the t-distribution.Example=TINV(0.1;6) returns 1.94TTEST functionTTESTReturns the probability associated with a Student's t-Test.SyntaxTTEST(Data1; Data2; Mode; Type)Data1 is the dependent array or range of data for the first record.Data2 is the dependent array or range of data for the second record.Mode = 1 calculates the one-tailed test, Mode = 2 the two- tailed test.Type is the kind of t-test to perform. Type 1 means paired. Type 2 means two samples, equal variance (homoscedastic). Type 3 means two samples, unequal variance (heteroscedastic).Example=TTEST(A1:A50;B1:B50;2;2)TDIST functiont-distributionTDISTReturns the t-distribution.SyntaxTDIST(Number; DegreesFreedom; Mode)Number is the value for which the t-distribution is calculated.DegreesFreedom is the number of degrees of freedom for the t-distribution.Mode = 1 returns the one-tailed test, Mode = 2 returns the two-tailed test.Example=TDIST(12;5;1)VAR functionvariancesVAREstimates the variance based on a sample.SyntaxVAR(Number1; Number2; ...Number30)Number1, Number2, ...Number30 are numerical values or ranges representing a sample based on an entire population.Example=VAR(A1:A50)VARA functionVARAEstimates a variance based on a sample. The value of text is 0.SyntaxVARA(Value1; Value2; ...Value30)Value1, Value2,...Value30 are values or ranges representing a sample derived from an entire population. Text has the value 0.Example=VARA(A1:A50)VARP functionVARPCalculates a variance based on the entire population.SyntaxVARP(Number1; Number2; ...Number30)Number1, Number2, ...Number30 are numerical values or ranges representing an entire population.Example=VARP(A1:A50)VARPA functionVARPACalculates the variance based on the entire population. The value of text is 0.SyntaxVARPA(Value1; Value2; ...Value30)Value1,value2,...Value30 are values or ranges representing an entire population.Example=VARPA(A1:A50)PERMUT functionnumber of permutationsPERMUTReturns the number of permutations for a given number of objects.SyntaxPERMUT(Count1; Count2)Count1 is the total number of objects.Count2 is the number of objects in each permutation.Example=PERMUT(6;3) returns 120. There are 120 different possibilities, to pick a sequence of 3 playing cards out of 6 playing cards.PERMUTATIONA functionPERMUTATIONAReturns the number of permutations for a given number of objects (repetition allowed).SyntaxPERMUTATIONA(Count1; Count2)Count1 is the total number of objects.Count2 is the number of objects in each permutation.ExampleHow often can 2 objects be selected from a total of 11 objects?=PERMUTATIONA(11;2) returns 121.=PERMUTATIONA(6;3) returns 216. There are 216 different possibilities to put a sequence of 3 playing cards together out of six playing cards if every card is returned before the next one is drawn.PROB functionPROBReturns the probability that values in a range are between two limits. If there is no End value, this function calculates the probability based on the principle that the Data values are equal to the value of Start.SyntaxPROB(Data; Probability; Start; End)Data is the array or range of data in the sample.Probability is the array or range of the corresponding probabilities.Start is the start value of the interval whose probabilities are to be summed.End (optional) is the end value of the interval whose probabilities are to be summed. If this parameter is missing, the probability for the Start value is calculated.Example=PROB(A1:A50;B1:B50;50;60) returns the probability with which a value within the range of A1:A50 is also within the limits between 50 and 60. Every value within the range of A1:A50 has a probability within the range of B1:B50.WEIBULL functionWEIBULLReturns the values of the Weibull distribution.The Weibull distribution is a continuous probability distribution, with parameters Alpha > 0 (shape) and Beta > 0 (scale). If C is 0, WEIBULL calculates the probability density function.If C is 1, WEIBULL calculates the cumulative distribution function.SyntaxWEIBULL(Number; Alpha; Beta; C)Number is the value at which to calculate the Weibull distribution.Alpha is the shape parameter of the Weibull distribution.Beta is the scale parameter of the Weibull distribution.C indicates the type of function.Example=WEIBULL(2;1;1;1) returns 0.86.See also the Wiki page.