Difference between revisions of "Documentation/How Tos/Calc: FTEST function"
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== FTEST == | == FTEST == | ||
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=== Issues: === | === Issues: === | ||
− | * Earlier versions of Excel and the ODFF | + | * Earlier versions of Excel and the ODFF specification incorrectly claimed this was a one-tailed test. |
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* [[Documentation/How_Tos/Calc: FDIST function|FDIST]] | * [[Documentation/How_Tos/Calc: FDIST function|FDIST]] | ||
* [[Documentation/How_Tos/Using Arrays|Array formulas]] | * [[Documentation/How_Tos/Using Arrays|Array formulas]] | ||
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* [[Documentation/How_Tos/Calc: Functions listed by category|Functions listed by category]]}} | * [[Documentation/How_Tos/Calc: Functions listed by category|Functions listed by category]]}} | ||
− | [[Category: Documentation/Reference/Calc]] | + | [[Category: Documentation/Reference/Calc/Statistical functions]] |
Latest revision as of 13:55, 2 February 2024
Spreadsheet Lookup functions
Measures of dispersion / spread
Probability and statistics
Correlation and line fitting
See also (in the Arrays Functions category); GROWTH, LINEST, LOGEST, TREND
Ranking
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FTEST
Returns the result of an F-test.
Syntax:
FTEST(data1; data2)
- data1 and data2 are ranges or arrays (possibly of different size) containing numbers, on which the F-test is performed. The F-test calculates the likelihood that two samples have the same variance.
- In effect, the sample variances of data1 and data2 are calculated. data1 and data2 are re-ordered if necessary so that data1 has the larger variance (σ1) and data2 the smaller (σ2), and an F_value is calculated as σ1/σ2. The result returned by FTEST is 2*FDIST(F_value; COUNT(data1)-1; COUNT(data2)-1). This is the two-tailed probability that the variances in data1 and data2 are not significantly different. (The internal algorithms used by Calc are more sophisticated than this).
- Advanced topic:
- The parameters data1 and data2 are always evaluated as array formulas.
Example:
FTEST({9;8;6;8}; {5;6;7})
- returns approximately 0.82. The probability that the variances of these two samples are not significantly different is about 82%. Note: a real world example would need more data than this.
Issues:
- Earlier versions of Excel and the ODFF specification incorrectly claimed this was a one-tailed test.
{{#switch:EN
| RU = Смотрите также:
| UA = Дивіться також:
| EN = See Also
| PT = Ver também
| #default = See Also
}}