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Premium plugin : Formulas statistics
Guillaume Bonnaire edited this page Jul 10, 2023
·
13 revisions
You can buy this plugin on Repo plugin formulas statistics Demo is available on demo formula
add formulas based on jStat(javascript) :
- ARITHMETICMEAN
- CUBICMEAN
- GASTWIRTHCOHENMEAN
- GEOMETRICMEAN
- HARMONICMEAN
- MEDIAN
- MIDRANGE
- MODE
- ROOTMEANSQUARE
- WINSORISEDMEAN
- BARNARDSTEST (WALD, NUISANCE, PONTAILED, PTWOTAILED)
- BINOMIALTEST (PEXACTLY, PFEWER, PATMOST, PMORE, PATLEAST)
- CHISQUAREDTEST (PEARSONCHISQUARED, DEGREESOFFREEDOM, SIGNIFICANCE)
- FISHERSEXACTTEST
- MANNWHITNEYU (ZSCORE, PONETAILED, PTWOTAILED)
- SIGNTEST (PMORE, PATLEAST)
- STUDENTSTTESTONESAMPLE (TSTATISTIC, DEGREESOFFREEDOM, PONESIDED, PTWOSIDED)
- STUDENTSTTESTTWOSAMPLES (TSTATISTIC, DEGREESOFFREEDOM, PONESIDED, PTWOSIDED)
- ANOVA (FSCORE, FTEST)
- JSpreadsheet Pro v8 of JSpreadsheet Pro v9 and Formula-Pro
- Compatible with plugin tooltip
none
none
You can overwrite documentation of formulas, by default, this documentation is the same of documentation JStat. For write your documentation, set documentation on the var jspreadsheet.formulasDoc
1 item of jspreadsheet.formulasDoc is construct like :
jspreadsheet.formulasDoc['MYFUNCTION()'] = {
syntax:"MYFUNCTION(value, value)",
about:"My custom function description ",
examples:"MYFUNCTION(2008, 7) equals 25",
params:[
{type:"Float", comment:"First value"},
{type:"Float", comment:"Second value"}
],
link:"https://mydocs.domain.ext/doc/123456"
};Important on jspreadsheet.formulasDoc object, define key property formula with () to end else it considers it as a variable.
| Property name | Description |
|---|---|
syntax |
Syntax of your formula |
description |
Description of your formula |
examples |
Example of your formula |
params (Array) |
Array for description parameters with for 1 param : type and comment
|
link |
Link for external documentation |
<script src="https://jsuites.net/v4/jsuites.js"></script>
<link rel="stylesheet" href="https://jsuites.net/v4/jsuites.css" type="text/css" />
<script src="https://jspreadsheet.com/v8/jspreadsheet.js"></script>
<link rel="stylesheet" href="https://jspreadsheet.com/v8/jspreadsheet.css" type="text/css" />
<script src="http://www.jspreadsheet.com/v8/plugins/formula.js"></script>
<!-- Optional -->
<script src="plugins/premiums/jss.tooltip.js"></script>
<link rel="stylesheet" href="plugins/premiums/jss.tooltip.css" type="text/css" />
<!-- init plugins statistics -->
<script>
// Initialisation
//Precision
formula.adjustPrecision = true;
// Extensions
jspreadsheet.setExtensions({ formula, statistics });
</script>Initialize plugin on JSpreadsheet
jspreadsheet(document.getElementById('spreadsheet'), {
...
plugins: [
...
{ name:'tooltip', plugin:jss_tooltip }, // Optional
...
],
...
});Range: Range of cells (A1:A3)| Syntax | Parameters | About | Example | Result of Example |
| MEAN.ARITMETIC(Range) |
Range: Range of cells (A1:A3)
|
Measures of central tendency: Computes the arithmetic mean of the values in a dataset. | =MEAN.ARITMETIC(1, 3, 7, 4, 12, 4, 4, 7, 3, 6, 7, 1, 2) | 4.69230… |
| MEAN.CUBIC(Range) |
Range: Range of cells (A1:A3)
|
Measures of central tendency: Computes the cubic mean of the values in a dataset. | =MEAN.CUBIC(1, 3, 7, 4, 12, 4, 4, 7, 3, 6, 7, 1, 2) | 6.28600… |
| MEAN.GASTWIRTHCOHEN(Range, [alpha=0.25], [lambda=0.25]) |
Range: Range of cells (A1:A3)
Alpha: Optional, Default: 0.25, must be within the range of [0, 0.5]
Lambda: Optional, Default: 0.25, must be within the range of [0, 0.5]
|
Measures of central tendency: Computes the Gastwirth-Cohen mean of the values in a dataset. alpha and lambda must be within the range of [0, 0.5]. If the scale of measure of the column given by data is not ordinal or of higher order or if alpha or lambda are outside of the range of [0, 0.5], it will return an error. | =MEAN.GASTWIRTHCOHEN([1, 3, 7, 4, 12, 4, 6, 7, 1, 2], 0.3, 0.1) | 4.1000… |
| MEAN.GEOMETRIC(Range) |
Range: Range of cells (A1:A3)
|
Measures of central tendency: Computes the geometric mean of the values in a dataset. If any non-positive values are supplied, this method will return undefined. | =MEAN.GEOMETRIC(1, 3, 7, 4, 12, 4, 4, 7, 3, 6, 7, 1, 2) | 3.74447… |
| MEAN.HARMONIC(Range) |
Range: Range of cells (A1:A3)
|
Measures of central tendency: Computes the harmonic mean of the values in a dataset. | =MEAN.HARMONIC(1, 3, 7, 4, 12, 4, 4, 7, 3, 6, 7, 1, 2) | 2.82901… |
| MEDIAN(Range) | Range: Range of cells (A1:A3) |
Measures of central tendency: Retrieves the median of a dataset. | =MEDIAN(1, 3, 7, 4, 12, 4, 4, 7, 3, 6, 7, 1, 2) | 4 |
| MIDRANGE(Range) |
Range: Range of cells (A1:A3)
|
Measures of central tendency: Computes the mid-range of a dataset. If the scale of measure of the column given by data is not ordinal or of higher order, it will return an error | =MIDRANGE(1, 3, 7, 4, 12, 4, 4, 7, 3, 6, 7, 1, 2) | 6.5 |
| MODE(Range) |
Range: Range of cells (A1:A3)
|
Measures of central tendency: Retrieves the most frequent value in a dataset. If there are two or more most common values of equal frequency, an array with these values will be returned. | =MODE(1, 3, 7, 4, 12, 4, 4, 7, 3, 6, 7, 1, 2) | [4, 7] |
| RMS(Range) |
Range: Range of cells (A1:A3)
|
Measures of central tendency: Computes the root mean square of the values in a dataset. If the scale of measure of the column given by data is not interval or of higher order, it will return an error. | =RMS(1, 3, 7, 4, 12, 4, 4, 7, 3, 6, 7, 1, 2) | 5.54006… |
| MEAN.WINSORISED(Range, [percentage=0.2]) |
Range: Range of cells (A1:A3)
Optional: Percentage: must be in range [0, 0.5], Default 0.2
|
Measures of central tendency: Computes the Winsorised (truncated) mean of the values in a dataset. Note, that for every truncated value of the sorted list, the now most extreme value will be repeated in its place, e.g. in a 10% truncated list of twenty values both the originally third and the 18th value in order will be repeated twice in order to replace the truncated first, second and 19th and 20th values, respectively. It’s commonly used to discard outliers that are within the outermost percentage per cent of values on either end of the full range. percentage must be an integer or floating point number within the range of [0, 0.5]. If the scale of measure of the column given by data is not interval or of higher order, it will return an error | =MEAN.WINSORISED([1, 3, 7, 4, 12, 4, 4, 7, 3, 6, 7, 1, 2], 0.33) | 4.38461… |
| BARNARDSTEST.WALD(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return wald value of barnardsTest Statistical tests - nonparametric: Computes Barnard’s exact test for two nominal, dichotomous (i.e. no more than two manifestations) variables firstColumn and secondColumn. Its result gives the exact probability that the particular observations in the given data can be made if the null hypothesis that both variables are independent from another holds true. however it is computationally more resource demanding. This method returns an object storing the Wald statistic wald, the one- and two-tailed significance and the nuisance parameter nuisance for which this significance is largest. |
=BARNARDSTEST.WALD(["female","female","female","female","female","female","female","female","male","male","male","male","male","male","male","male","male"],["yes","yes","no","no","no","no","no","no","yes","yes","yes","yes","yes","yes","yes","no","no"]) | -2.17608… |
| BARNARDSTEST.NUISANCE(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return nuisance value of barnardsTest Statistical tests - nonparametric: Computes Barnard’s exact test for two nominal, dichotomous (i.e. no more than two manifestations) variables firstColumn and secondColumn. Its result gives the exact probability that the particular observations in the given data can be made if the null hypothesis that both variables are independent from another holds true. however it is computationally more resource demanding. This method returns an object storing the Wald statistic wald, the one- and two-tailed significance and the nuisance parameter nuisance for which this significance is largest. |
=BARNARDSTEST.NUISANCE(["female","female","female","female","female","female","female","female","male","male","male","male","male","male","male","male","male"],["yes","yes","no","no","no","no","no","no","yes","yes","yes","yes","yes","yes","yes","no","no"]) | 0.50001… |
| BARNARDSTEST.P1TAILED(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return pOneTailed value of barnardsTest Statistical tests - nonparametric: Computes Barnard’s exact test for two nominal, dichotomous (i.e. no more than two manifestations) variables firstColumn and secondColumn. Its result gives the exact probability that the particular observations in the given data can be made if the null hypothesis that both variables are independent from another holds true. however it is computationally more resource demanding. This method returns an object storing the Wald statistic wald, the one- and two-tailed significance and the nuisance parameter nuisance for which this significance is largest. |
=BARNARDSTEST.P1TAILED(["female","female","female","female","female","female","female","female","male","male","male","male","male","male","male","male","male"],["yes","yes","no","no","no","no","no","no","yes","yes","yes","yes","yes","yes","yes","no","no"]) | 0.02452… |
| BARNARDSTEST.P2TAILED(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return pTwoTailed value of barnardsTest Statistical tests - nonparametric: Computes Barnard’s exact test for two nominal, dichotomous (i.e. no more than two manifestations) variables firstColumn and secondColumn. Its result gives the exact probability that the particular observations in the given data can be made if the null hypothesis that both variables are independent from another holds true. however it is computationally more resource demanding. This method returns an object storing the Wald statistic wald, the one- and two-tailed significance and the nuisance parameter nuisance for which this significance is largest. |
=BARNARDSTEST.P2TAILED(["female","female","female","female","female","female","female","female","male","male","male","male","male","male","male","male","male"],["yes","yes","no","no","no","no","no","no","yes","yes","yes","yes","yes","yes","yes","no","no"]) | 0.04904… |
| BINOMIALTEST.PEXACTLY(Range, valueToTest, [alpha=0.5]) |
Range: Range of cells (A1:A3)
valueToTest: String
Alpha: Optional, Default: 0.5
|
Return pExactly value of binomialTest Statistical tests - nonparametric: Computes the binomial test for the values of a nominal, dichotomous (i.e. no more than two manifestations) variable data that can be either the name of a column (string) or an array of values. Its result is the probability that the observation of the values of data could be made if the event valueToTest is assumed to happen with a chance of alpha. This method returns the test result for exactly, fewer (or exactly), and more (or exactly) as many events valueToTest can be observed. |
=BINOMIALTEST.PEXACTLY(["no","no","no","no","no","no","no","yes","yes","yes","yes","yes"], "yes", 0.8) | 0.00332… |
| BINOMIALTEST.PFEWER(Range, valueToTest, [alpha=0.5]) |
Range: Range of cells (A1:A3)
valueToTest: String
Alpha: Optional, Default: 0.5
|
Return pFewer value of binomialTest Statistical tests - nonparametric: Computes the binomial test for the values of a nominal, dichotomous (i.e. no more than two manifestations) variable data that can be either the name of a column (string) or an array of values. Its result is the probability that the observation of the values of data could be made if the event valueToTest is assumed to happen with a chance of alpha. This method returns the test result for exactly, fewer (or exactly), and more (or exactly) as many events valueToTest can be observed. |
=BINOMIALTEST.PFEWER(["no","no","no","no","no","no","no","yes","yes","yes","yes","yes"], "yes", 0.8) | 0.00058… |
| BINOMIALTEST.PATMOST(Range, valueToTest, [alpha=0.5]) |
Range: Range of cells (A1:A3)
valueToTest: String
Alpha: Optional, Default: 0.5
|
Return pAtMost value of binomialTest Statistical tests - nonparametric: Computes the binomial test for the values of a nominal, dichotomous (i.e. no more than two manifestations) variable data that can be either the name of a column (string) or an array of values. Its result is the probability that the observation of the values of data could be made if the event valueToTest is assumed to happen with a chance of alpha. This method returns the test result for exactly, fewer (or exactly), and more (or exactly) as many events valueToTest can be observed. |
=BINOMIALTEST.PATMOST(["no","no","no","no","no","no","no","yes","yes","yes","yes","yes"], "yes", 0.8) | 0.00390… |
| BINOMIALTEST.PMORE(Range, valueToTest, [alpha=0.5]) |
Range: Range of cells (A1:A3)
valueToTest: String
Alpha: Optional, Default: 0.5
|
Return pMore value of binomialTest Statistical tests - nonparametric: Computes the binomial test for the values of a nominal, dichotomous (i.e. no more than two manifestations) variable data that can be either the name of a column (string) or an array of values. Its result is the probability that the observation of the values of data could be made if the event valueToTest is assumed to happen with a chance of alpha. This method returns the test result for exactly, fewer (or exactly), and more (or exactly) as many events valueToTest can be observed. |
=BINOMIALTEST.PMORE(["no","no","no","no","no","no","no","yes","yes","yes","yes","yes"], "yes", 0.8) | 0.99609… |
| BINOMIALTEST.PATLEAST(Range, valueToTest, [alpha=0.5]) |
Range: Range of cells (A1:A3)
valueToTest: String
Alpha: Optional, Default: 0.5
|
Return pAtLeast value of binomialTest Statistical tests - nonparametric: Computes the binomial test for the values of a nominal, dichotomous (i.e. no more than two manifestations) variable data that can be either the name of a column (string) or an array of values. Its result is the probability that the observation of the values of data could be made if the event valueToTest is assumed to happen with a chance of alpha. This method returns the test result for exactly, fewer (or exactly), and more (or exactly) as many events valueToTest can be observed. |
=BINOMIALTEST.PATLEAST(["no","no","no","no","no","no","no","yes","yes","yes","yes","yes"], "yes", 0.8) | 0.99941… |
| CHITEST.PCHISQUARED(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return PearsonChiSquared value of chiSquaredTest Statistical tests - nonparametric: Computes the Chi-squared test for two ordinal or nominal variables firstColumn and secondColumn. Its result gives the exact probability that the particular observations in the given data can be made if the null hypothesis that both variables are independent from another holds true. |
=CHITEST.PCHISQUARED(A1:A6,B1:B6) | 0.04146… |
| CHITEST.DF(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return degreesOfFreedom value of chiSquaredTest Statistical tests - nonparametric: Computes the Chi-squared test for two ordinal or nominal variables firstColumn and secondColumn. Its result gives the exact probability that the particular observations in the given data can be made if the null hypothesis that both variables are independent from another holds true. |
=CHITEST.DF(A1:A6,B1:B6) | -1.91880… |
| CHITEST.SIGNIFICANCE(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return significance value of chiSquaredTest Statistical tests - nonparametric: Computes the Chi-squared test for two ordinal or nominal variables firstColumn and secondColumn. Its result gives the exact probability that the particular observations in the given data can be made if the null hypothesis that both variables are independent from another holds true. |
=CHITEST.SIGNIFICANCE(A1:A6,B1:B6) | 0.02749… |
| FISHERSEXACTTEST(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Statistical tests - nonparametric: Computes
Barnard’s exact test for two nominal, dichotomous (i.e. no more than two
manifestations) variables firstColumn and secondColumn. Its result gives
the exact probability that the particular observations in the given data
can be made if the null hypothesis that both variables are independent
from another holds true. however it is computationally more resource
demanding. This method returns an object storing the Wald statistic wald, the one- and two-tailed significance and the nuisance parameter nuisance for which this significance is largest. |
=FISHERSEXACTTEST(["female","female","female","female","female","female","female","female","male","male","male","male","male","male","male","male","male"],["yes","yes","no","no","no","no","no","no","yes","yes","yes","yes","yes","yes","yes","no","no"]) | 0.05499… |
| MANNWUTEST.ZSCORE(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return zScore value of mannWhitneyU Statistical tests - nonparametric: Performs the Mann-Whitney U test on the values of firstColumn assigned to the two groups given by the variable secondColumn. It tests the null hypothesis that it is equally likely that a randomly selected sample from one group is less or greater than another from the other group. This test compares the rank sums of the observed data and computes a statistic that is normally distributed, however does not require the assumption of a normally distributed variable. This method returns the Mann-Whitney U along with its associated z-score and both p-values for one- and two-sided null hypotheses. |
=MANNWUTEST.ZSCORE(["MALE", "FEMALE", "MALE", "FEMALE", "FEMALE", "MALE", "FEMALE", "FEMALE", "FEMALE", "MALE"],[2150, 1800, 2300, 1600, 1700, 2000, 1850, 2200, 1750, 2050]) | 2 |
| MANNWUTEST.P1TAILED(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return pOneTailed value of mannWhitneyU Statistical tests - nonparametric: Performs the Mann-Whitney U test on the values of firstColumn assigned to the two groups given by the variable secondColumn. It tests the null hypothesis that it is equally likely that a randomly selected sample from one group is less or greater than another from the other group. This test compares the rank sums of the observed data and computes a statistic that is normally distributed, however does not require the assumption of a normally distributed variable. This method returns the Mann-Whitney U along with its associated z-score and both p-values for one- and two-sided null hypotheses. |
=MANNWUTEST.P1TAILED(["MALE", "FEMALE", "MALE", "FEMALE", "FEMALE", "MALE", "FEMALE", "FEMALE", "FEMALE", "MALE"],[2150, 1800, 2300, 1600, 1700, 2000, 1850, 2200, 1750, 2050]) | 0.04394… |
| MANNWUTEST.P2TAILED(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return pTwoTailed value of mannWhitneyU Statistical tests - nonparametric: Performs the Mann-Whitney U test on the values of firstColumn assigned to the two groups given by the variable secondColumn. It tests the null hypothesis that it is equally likely that a randomly selected sample from one group is less or greater than another from the other group. This test compares the rank sums of the observed data and computes a statistic that is normally distributed, however does not require the assumption of a normally distributed variable. This method returns the Mann-Whitney U along with its associated z-score and both p-values for one- and two-sided null hypotheses. |
=MANNWUTEST.P2TAILED(["MALE", "FEMALE", "MALE", "FEMALE", "FEMALE", "MALE", "FEMALE", "FEMALE", "FEMALE", "MALE"],[2150, 1800, 2300, 1600, 1700, 2000, 1850, 2200, 1750, 2050]) | 0.01074… |
| SIGNTEST.POSITIVES(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return positives value of signTest Statistical tests - nonparametric: Computes the sign test for two variables firstColumn and secondColumn by comparing the values in pairs of observations and counting the amount of pairs where the value for firstColumn is larger than that for secondColumn, returned as positives. The order of these variables is therefore important, i.e. all calculated significance parameters should be interpreted in regard to the number of positives under the assumption that the null hypothesis of equally likelihood that any pair can yield a negative or a positive difference. |
=SIGNTEST.POSITIVES([80, 78, 92, 76, 94, 93, 82, 104, 74, 84],[83, 82, 94, 64, 96, 97, 83, 87, 77, 85]) | 0.05468… |
| SIGNTEST.PEXACTLY(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return pExactly value of signTest Statistical tests - nonparametric: Computes the sign test for two variables firstColumn and secondColumn by comparing the values in pairs of observations and counting the amount of pairs where the value for firstColumn is larger than that for secondColumn, returned as positives. The order of these variables is therefore important, i.e. all calculated significance parameters should be interpreted in regard to the number of positives under the assumption that the null hypothesis of equally likelihood that any pair can yield a negative or a positive difference. |
=SIGNTEST.PEXACTLY([80, 78, 92, 76, 94, 93, 82, 104, 74, 84],[83, 82, 94, 64, 96, 97, 83, 87, 77, 85]) | 0.94531… |
| SIGNTEST.PFEWER(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return pFewer value of signTest Statistical tests - nonparametric: Computes the sign test for two variables firstColumn and secondColumn by comparing the values in pairs of observations and counting the amount of pairs where the value for firstColumn is larger than that for secondColumn, returned as positives. The order of these variables is therefore important, i.e. all calculated significance parameters should be interpreted in regard to the number of positives under the assumption that the null hypothesis of equally likelihood that any pair can yield a negative or a positive difference. |
=SIGNTEST.PFEWER([80, 78, 92, 76, 94, 93, 82, 104, 74, 84],[83, 82, 94, 64, 96, 97, 83, 87, 77, 85]) | 0.94531… |
| SIGNTEST.PATMOST(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return pAtMost value of signTest Statistical tests - nonparametric: Computes the sign test for two variables firstColumn and secondColumn by comparing the values in pairs of observations and counting the amount of pairs where the value for firstColumn is larger than that for secondColumn, returned as positives. The order of these variables is therefore important, i.e. all calculated significance parameters should be interpreted in regard to the number of positives under the assumption that the null hypothesis of equally likelihood that any pair can yield a negative or a positive difference. |
=SIGNTEST.PATMOST([80, 78, 92, 76, 94, 93, 82, 104, 74, 84],[83, 82, 94, 64, 96, 97, 83, 87, 77, 85]) | -3.51631… |
| SIGNTEST.PMORE(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return pMore value of signTest Statistical tests - nonparametric: Computes the sign test for two variables firstColumn and secondColumn by comparing the values in pairs of observations and counting the amount of pairs where the value for firstColumn is larger than that for secondColumn, returned as positives. The order of these variables is therefore important, i.e. all calculated significance parameters should be interpreted in regard to the number of positives under the assumption that the null hypothesis of equally likelihood that any pair can yield a negative or a positive difference. |
=SIGNTEST.PMORE([80, 78, 92, 76, 94, 93, 82, 104, 74, 84],[83, 82, 94, 64, 96, 97, 83, 87, 77, 85]) | 9 |
| SIGNTEST.PATLEAST(firstColumn: Range, secondColumn: Range) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
|
Return pAtLeast value of signTest Statistical tests - nonparametric: Computes the sign test for two variables firstColumn and secondColumn by comparing the values in pairs of observations and counting the amount of pairs where the value for firstColumn is larger than that for secondColumn, returned as positives. The order of these variables is therefore important, i.e. all calculated significance parameters should be interpreted in regard to the number of positives under the assumption that the null hypothesis of equally likelihood that any pair can yield a negative or a positive difference. |
=SIGNTEST.PATLEAST([80, 78, 92, 76, 94, 93, 82, 104, 74, 84],[83, 82, 94, 64, 96, 97, 83, 87, 77, 85]) | 0.00327… |
| TTEST.ONESAMPLE.T(Range, nullHypothesisMean) |
Range: Range of cells (A1:A3)
nullHypothesisMean: number
|
Return tStatistic value of studentsTTestOneSample Statistical tests - parametric: Computes Student’s one sample t-test for the values of a variable given by column. It examines if the arithmetic mean of a sample column is equal to the predefined or suspected arithmetic mean nullHypothesisMean. This method returns the associated t-statistic, the degrees of freedom and both one- and two-sided probabilities that the given observation can be made if the null hypothesis of equal arithmetic means is to hold true. |
=TTEST.ONESAMPLE.T([185, 201, 193, 184, 180, 176, 193, 182, 197, 204], 200) | 0.00655… |
| TTEST.ONESAMPLE.DF(Range, nullHypothesisMean) |
Range: Range of cells (A1:A3)
nullHypothesisMean: number
|
Return degreesOfFreedom value of studentsTTestOneSample Statistical tests - parametric: Computes Student’s one sample t-test for the values of a variable given by column. It examines if the arithmetic mean of a sample column is equal to the predefined or suspected arithmetic mean nullHypothesisMean. This method returns the associated t-statistic, the degrees of freedom and both one- and two-sided probabilities that the given observation can be made if the null hypothesis of equal arithmetic means is to hold true. |
=TTEST.ONESAMPLE.DF([185, 201, 193, 184, 180, 176, 193, 182, 197, 204], 200) | 3.79663… |
| TTEST.ONESAMPLE.P1SIDED(Range, nullHypothesisMean) |
Range: Range of cells (A1:A3)
nullHypothesisMean: number
|
Return pOneSided value of studentsTTestOneSample Statistical tests - parametric: Computes Student’s one sample t-test for the values of a variable given by column. It examines if the arithmetic mean of a sample column is equal to the predefined or suspected arithmetic mean nullHypothesisMean. This method returns the associated t-statistic, the degrees of freedom and both one- and two-sided probabilities that the given observation can be made if the null hypothesis of equal arithmetic means is to hold true. |
=TTEST.ONESAMPLE.P1SIDED([185, 201, 193, 184, 180, 176, 193, 182, 197, 204], 200) | 9 |
| TTEST.ONESAMPLE.P2SIDED(Range, nullHypothesisMean) |
Range: Range of cells (A1:A3)
nullHypothesisMean: number
|
Return pTwoSided value of studentsTTestOneSample Statistical tests - parametric: Computes Student’s one sample t-test for the values of a variable given by column. It examines if the arithmetic mean of a sample column is equal to the predefined or suspected arithmetic mean nullHypothesisMean. This method returns the associated t-statistic, the degrees of freedom and both one- and two-sided probabilities that the given observation can be made if the null hypothesis of equal arithmetic means is to hold true. |
=TTEST.ONESAMPLE.P2SIDED([185, 201, 193, 184, 180, 176, 193, 182, 197, 204], 200) | 0 |
| TTEST.TWOSAMPLES.T(firstColumn: Range, secondColumn: Range[, pairedSamples: Boolean = FALSE]) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
pairedSamples(Optional): calculation with dependant values, default false
|
Return tStatistic value of studentsTTestTwoSamples Statistical tests - parametric: Computes Student’s two sample t-test for the values of two variables given by firstColumn and secondColumn. |
=TTEST.TWOSAMPLES.T([204, 212, 199, 209, 191, 190, 223, 185, 206, 212],[189, 199, 191, 182, 176, 180, 220, 182, 194, 216]) | 0.00211… |
| TTEST.TWOSAMPLES.DF(firstColumn: Range, secondColumn: Range[, pairedSamples: Boolean = FALSE]) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
pairedSamples(Optional): calculation with dependant values, default false
|
Return degreesOfFreedom value of studentsTTestTwoSamples Statistical tests - parametric: Computes Student’s two sample t-test for the values of two variables given by firstColumn and secondColumn. |
=TTEST.TWOSAMPLES.DF([204, 212, 199, 209, 191, 190, 223, 185, 206, 212],[189, 199, 191, 182, 176, 180, 220, 182, 194, 216]) | 0.00423… |
| TTEST.TWOSAMPLES.P1SIDED(firstColumn: Range, secondColumn: Range[, pairedSamples: Boolean = FALSE]) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
pairedSamples(Optional): calculation with dependant values, default false
|
Return pOneSided value of studentsTTestTwoSamples Statistical tests - parametric: Computes Student’s two sample t-test for the values of two variables given by firstColumn and secondColumn. |
=TTEST.TWOSAMPLES.P1SIDED([204, 212, 199, 209, 191, 190, 223, 185, 206, 212],[189, 199, 191, 182, 176, 180, 220, 182, 194, 216]) | 0.10557… |
| TTEST.TWOSAMPLES.P2SIDED(firstColumn: Range, secondColumn: Range[, pairedSamples: Boolean = FALSE]) |
firstColumn Range: Range of cells (A1:A3)
secondColumn Range: Range of cells (B1:B3), Need same size of firstColumn
pairedSamples(Optional): calculation with dependant values, default false
|
Return pTwoSided value of studentsTTestTwoSamples Statistical tests - parametric: Computes Student’s two sample t-test for the values of two variables given by firstColumn and secondColumn. |
=TTEST.TWOSAMPLES.P2SIDED([204, 212, 199, 209, 191, 190, 223, 185, 206, 212],[189, 199, 191, 182, 176, 180, 220, 182, 194, 216]) | |
| ANOVA.FSCORE(Range 1, Range 2, ..., Range n) |
Range: Range of cells (A1:A3)
|
Returns the f-score of an ANOVA on the arrays (Range). | =ANOVA.FSCORE([1,2], [3,4]) | |
| ANOVA.FTEST(Range 1, Range 2, ..., Range n) |
Range: Range of cells (A1:A3)
|
Returns the p-value of the f-statistic from the ANOVA test on the arrays (Range). | =ANOVA.FTEST([1,2], [3,4]) |
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