Translation components API.

See the Weblate's Web API documentation for detailed description of the API.

GET /api/translations/libo_help-master/textscalc01/dz/units/?format=api&page=56
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            "source": [
                "<emph>Range</emph> is the range to which the criteria are to be applied."
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                "<emph> ཁྱབ་ཚད་དེ་ </emph> ཁྱད་ཚད་ཚུ་འཇུག་སྤྱོད་འབད་ནི་ཨིན་པའི་ ཁྱབ་ཚད་ཨིན།"
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                "A1:A10 is a cell range containing the numbers <item type=\"input\">2000</item> to <item type=\"input\">2009</item>. Cell B1 contains the number <item type=\"input\">2006</item>. In cell B2, you enter a formula:"
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                "<item type=\"input\">=COUNTIF(A1:A10;2006)</item> - this returns 1."
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                "<item type=\"input\">=COUNTIF(A1:A10;\">=2006\")</item> - this returns 4."
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                "<item type=\"input\">=COUNTIF(A1:A10;\"<\"&B1)</item> - when B1 contains <item type=\"input\">2006</item>, this returns 6."
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                "<item type=\"input\">=COUNTIF(A1:A10;C2)</item> where cell C2 contains the text <item type=\"input\">>2006</item> counts the number of cells in the range A1:A10 which are >2006."
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            "source": [
                "To count only negative numbers: <item type=\"input\">=COUNTIF(A1:A10;\"<0\")</item>"
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            "source": [
                "<bookmark_value>B function</bookmark_value>  <bookmark_value>probabilities of samples with binomial distribution</bookmark_value>"
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                "<bookmark_value>B ལས་འགན་</bookmark_value><bookmark_value>དཔེ་ཚད་ཀྱི་འབྱུང་ངེས་ མིང་ཚིག་གཉིས་ལྡན་བགོ་བཀྲམ་དང་གཅིག་ཁར་</bookmark_value>"
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                "B"
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            "id": 1470946,
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            "source": [
                "<ahelp hid=\"HID_FUNC_B\">Returns the probability of a sample with binomial distribution.</ahelp>"
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                "<ahelp hid=\"HID_FUNC_B\"> མིང་ཚིག་གཉིས་ལྡན་བགོ་བཀྲམ་བཅས་པའི་དཔེ་ཚད་ཀྱི་ འབྱུང་འགྱུར་སླར་ལོག་འབདཝ་ཨིན། </ahelp>"
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            "source": [
                "<emph>Trials</emph> is the number of independent trials."
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                "<emph> སྔོན་རྟགས་ཟེར་མི་ཚུ་ </emph> སྔོན་རྟགས་རང་དབང་ཚུའི་གྱངས་ཁ་ཨིན།"
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                "<emph>SP</emph> is the probability of success on each trial."
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                "<emph> ཨེསི་པི་ </emph> ཟེར་མི་དེ་ སྔོན་རྟགས་རེ་རེར་གུ་མཐར་འཁྱོལ་གྱི་འབྱུང་འགྱུར་ཨིན།"
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                "<emph>T1</emph> defines the lower limit for the number of trials."
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                "<emph>T_1</emph> གིས་ སྔོན་རྟགས་ཚུའི་གྱངས་ཁའི་དོན་ལུ་ བཅད་མཚམས་འོག་མམ་དེ་ངེས་འཛིན་འབདཝ་ཨིན།"
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            "source": [
                "<emph>T2</emph> (optional) defines the upper limit for the number of trials."
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                "<emph>T_2</emph> (གདམ་ཁ་ཅན་) གིས་ སྔོན་རྟགས་ཚུའི་གྱངས་ཁའི་དོན་ལུ་ ལྟག་གི་བཅད་མཚམས་ངེས་འཛིན་འབདཝ་ཨིན།"
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            "id": 1470952,
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            "source": [
                "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:"
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                "དྲུག་དེ་ཏག་ཏག་སྦེ་ཚར་གཉིས་འོང་བའི་ ཤོ་ཚར་བཅུ་ཐམ་འཕང་བ་དང་བཅས་པའི་འབྱུང་འགྱུར་ག་ཅི་སྨོ? དྲུག་གི་འབྱུང་འགྱུར་དེ་ (ཡང་ན་ ཨང་གྲངས་གཞན་མི་གང་རུང་ཅིག་) ༡/༦ ཨིན།"
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                "<item type=\"input\">=B(10;1/6;2)</item> returns a probability of 29%."
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                ""
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            "priority": 100,
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            "source": [
                "<bookmark_value>RSQ function</bookmark_value>  <bookmark_value>determination coefficients</bookmark_value>  <bookmark_value>regression analysis</bookmark_value>"
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                "<bookmark_value>ཨར་ཨེསི་ཀིའུ་ལསའགན་</bookmark_value><bookmark_value>གཏན་འབེབས་བཟོ་ནིའི་གྲངས་རྟགས་ཚུ་</bookmark_value><bookmark_value>རི་གེ་རེ་ཤཱན་དཔྱད་ཞིབ་</bookmark_value>"
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                "RSQ"
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                "<ahelp hid=\"HID_FUNC_BESTIMMTHEITSMASS\">Returns the square of the Pearson correlation coefficient based on the given values.</ahelp> RSQ (also called determination coefficient) is a measure for the accuracy of an adjustment and can be used to produce a regression analysis."
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                "<ahelp hid=\"HID_FUNC_BESTIMMTHEITSMASS\"> གྲ་སྒྲིག་འབད་ཡོད་པའི་གནས་གོང་ཚུ་གུ་ལུ་གཞི་བཞག་སྟེ་ པི་ཡར་སཱོན་གྲངས་རྟགས་མཐུན་མོས་ཀྱི་འབྲེལ་བའི་གྲུ་བཞི་སླར་ལོག་འབདཝ་ཨིན། </ahelp> ཨར་ ཨེསི་ ཀིའུ་(ཡང་དེ་ལུ་ གཏན་འབེབས་བཟོ་བཟི་གྲངས་རྟགས་ཟེར་ཡང་སླབ་སྲོལ་ཡོད་) དེ་ བདེ་སྒྲིག་དོན་གྱི་ཏན་ཏན་དོན་ལུ་ཚད་འཇལ་གཅིག་ཨིནམ་ད་རི་གེ་རེ་ཤཱན་དཔྱད་ཞིབ་བཟོ་ནིའི་དོན་ལུ་ཡང་ལག་ལེན་འཐབ་བཏུབ་ཨིན།"
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                "<emph>DataY</emph> is an array or range of data points."
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                "<emph>Data_Y</emph> འདི་གནད་སྡུད་ས་ཚིགས་ཚུའི་ ཨེ་རེ་ཡང་ན་ ཁྱབ་ཚད་ཨིན།"
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                "<item type=\"input\">=RSQ(A1:A20;B1:B20)</item> calculates the determination coefficient for both data sets in columns A and B."
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                "=RSQ(A1:A20; B1:B20) ཀེར་ཐིག་ A དང་ B ཚུ་ནང་ གནད་སྡུད་ཆ་ཚན་གཉིས་ཆ་རའི་དོན་ལུ་ མཐུན་མོས་ཀྱི་འབྲེལ་བ་གྲངས་རྟགས་རྩིས་སྟོནམ་ཨིན།"
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                "BETAINV"
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                "<bookmark_value>BETADIST function</bookmark_value>  <bookmark_value>cumulative probability density function;calculating</bookmark_value>"
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                "BETADIST"
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                "<ahelp hid=\"HID_FUNC_BETAVERT\">Returns the beta function.</ahelp>"
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                "<emph>Number</emph> is the value between <emph>Start</emph> and <emph>End</emph> at which to evaluate the function."
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                "<emph>End</emph> (optional) is the upper bound for <emph>Number</emph>."
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                "<emph> མཇུག་ </emph> (གདམ་ཁ་ཅན་) དེ་ ཨང་གྲངས་དོན་ལུ་ <emph> ལྟག་གི་ </emph> བཅད་མཚམས་ཨིན།"
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                "<emph>Cumulative</emph> (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."
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                "<item type=\"input\">=BETADIST(0.75;3;4)</item> returns the value 0.96."
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                "<bookmark_value>BETA.DIST function</bookmark_value>  <bookmark_value>cumulative probability density function;calculating</bookmark_value>"
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                "BETA.DIST"
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            "id": 1470994,
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                "<ahelp hid=\"HID_FUNC_BETADIST_MS\">Returns the beta function.</ahelp>"
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                "<emph>Number</emph> (required) is the value between <emph>Start</emph> and <emph>End</emph> at which to evaluate the function."
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