The new concepts of measurement error’s regularities and effect characteristics

In several literatures, the authors give a new thinking of measurement theory system based on error non-classification philosophy, which completely overthrows the existing measurement concept system of precision, trueness and accuracy. In this paper, by focusing on the issues of error’s regularities...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Ye, Xiaoming [verfasserIn] Liu, Haibo [verfasserIn] Xiao, Xuebin [verfasserIn] Ling, Mo [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	Measurement error Function model Random model Error’s regularities Uncertainty

Übergeordnetes Werk:	Enthalten in: Measurement - Amsterdam [u.a.] : Elsevier Science, 1983, 126, Seite 65-71
Übergeordnetes Werk:	volume:126 ; pages:65-71

DOI / URN:	10.1016/j.measurement.2018.05.045

Katalog-ID:	ELV000559229

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520			\|a In several literatures, the authors give a new thinking of measurement theory system based on error non-classification philosophy, which completely overthrows the existing measurement concept system of precision, trueness and accuracy. In this paper, by focusing on the issues of error’s regularities and effect characteristics, the authors will do a thematic interpretation, and prove that the error’s regularities actually come from different cognitive perspectives, are also unable to be used for classifying errors, and that the error’s effect characteristics actually depend on artificial condition rules of repeated measurement, and are still unable to be used for classifying errors. Thus, from the perspectives of error’s regularities and effect characteristics, the existing error classification philosophy is still incorrect; and an uncertainty concept system, which must be interpreted by the error non-classification philosophy, naturally becomes the only way out of measurement theory.
650		4	\|a Measurement error
650		4	\|a Function model
650		4	\|a Random model
650		4	\|a Error’s regularities
650		4	\|a Uncertainty
700	1		\|a Liu, Haibo \|e verfasserin \|4 aut
700	1		\|a Xiao, Xuebin \|e verfasserin \|4 aut
700	1		\|a Ling, Mo \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Measurement \|d Amsterdam [u.a.] : Elsevier Science, 1983 \|g 126, Seite 65-71 \|h Online-Ressource \|w (DE-627)320404927 \|w (DE-600)2000550-7 \|w (DE-576)259484342 \|7 nnns
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936	b	k	\|a 50.21 \|j Messtechnik
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publishDate	2018
allfields	10.1016/j.measurement.2018.05.045 doi (DE-627)ELV000559229 (ELSEVIER)S0263-2241(18)30435-4 DE-627 ger DE-627 rda eng 660 DE-600 50.21 bkl Ye, Xiaoming verfasserin aut The new concepts of measurement error’s regularities and effect characteristics 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In several literatures, the authors give a new thinking of measurement theory system based on error non-classification philosophy, which completely overthrows the existing measurement concept system of precision, trueness and accuracy. In this paper, by focusing on the issues of error’s regularities and effect characteristics, the authors will do a thematic interpretation, and prove that the error’s regularities actually come from different cognitive perspectives, are also unable to be used for classifying errors, and that the error’s effect characteristics actually depend on artificial condition rules of repeated measurement, and are still unable to be used for classifying errors. Thus, from the perspectives of error’s regularities and effect characteristics, the existing error classification philosophy is still incorrect; and an uncertainty concept system, which must be interpreted by the error non-classification philosophy, naturally becomes the only way out of measurement theory. Measurement error Function model Random model Error’s regularities Uncertainty Liu, Haibo verfasserin aut Xiao, Xuebin verfasserin aut Ling, Mo verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 126, Seite 65-71 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:126 pages:65-71 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.21 Messtechnik AR 126 65-71
spelling	10.1016/j.measurement.2018.05.045 doi (DE-627)ELV000559229 (ELSEVIER)S0263-2241(18)30435-4 DE-627 ger DE-627 rda eng 660 DE-600 50.21 bkl Ye, Xiaoming verfasserin aut The new concepts of measurement error’s regularities and effect characteristics 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In several literatures, the authors give a new thinking of measurement theory system based on error non-classification philosophy, which completely overthrows the existing measurement concept system of precision, trueness and accuracy. In this paper, by focusing on the issues of error’s regularities and effect characteristics, the authors will do a thematic interpretation, and prove that the error’s regularities actually come from different cognitive perspectives, are also unable to be used for classifying errors, and that the error’s effect characteristics actually depend on artificial condition rules of repeated measurement, and are still unable to be used for classifying errors. Thus, from the perspectives of error’s regularities and effect characteristics, the existing error classification philosophy is still incorrect; and an uncertainty concept system, which must be interpreted by the error non-classification philosophy, naturally becomes the only way out of measurement theory. Measurement error Function model Random model Error’s regularities Uncertainty Liu, Haibo verfasserin aut Xiao, Xuebin verfasserin aut Ling, Mo verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 126, Seite 65-71 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:126 pages:65-71 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.21 Messtechnik AR 126 65-71
allfields_unstemmed	10.1016/j.measurement.2018.05.045 doi (DE-627)ELV000559229 (ELSEVIER)S0263-2241(18)30435-4 DE-627 ger DE-627 rda eng 660 DE-600 50.21 bkl Ye, Xiaoming verfasserin aut The new concepts of measurement error’s regularities and effect characteristics 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In several literatures, the authors give a new thinking of measurement theory system based on error non-classification philosophy, which completely overthrows the existing measurement concept system of precision, trueness and accuracy. In this paper, by focusing on the issues of error’s regularities and effect characteristics, the authors will do a thematic interpretation, and prove that the error’s regularities actually come from different cognitive perspectives, are also unable to be used for classifying errors, and that the error’s effect characteristics actually depend on artificial condition rules of repeated measurement, and are still unable to be used for classifying errors. Thus, from the perspectives of error’s regularities and effect characteristics, the existing error classification philosophy is still incorrect; and an uncertainty concept system, which must be interpreted by the error non-classification philosophy, naturally becomes the only way out of measurement theory. Measurement error Function model Random model Error’s regularities Uncertainty Liu, Haibo verfasserin aut Xiao, Xuebin verfasserin aut Ling, Mo verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 126, Seite 65-71 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:126 pages:65-71 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.21 Messtechnik AR 126 65-71
allfieldsGer	10.1016/j.measurement.2018.05.045 doi (DE-627)ELV000559229 (ELSEVIER)S0263-2241(18)30435-4 DE-627 ger DE-627 rda eng 660 DE-600 50.21 bkl Ye, Xiaoming verfasserin aut The new concepts of measurement error’s regularities and effect characteristics 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In several literatures, the authors give a new thinking of measurement theory system based on error non-classification philosophy, which completely overthrows the existing measurement concept system of precision, trueness and accuracy. In this paper, by focusing on the issues of error’s regularities and effect characteristics, the authors will do a thematic interpretation, and prove that the error’s regularities actually come from different cognitive perspectives, are also unable to be used for classifying errors, and that the error’s effect characteristics actually depend on artificial condition rules of repeated measurement, and are still unable to be used for classifying errors. Thus, from the perspectives of error’s regularities and effect characteristics, the existing error classification philosophy is still incorrect; and an uncertainty concept system, which must be interpreted by the error non-classification philosophy, naturally becomes the only way out of measurement theory. Measurement error Function model Random model Error’s regularities Uncertainty Liu, Haibo verfasserin aut Xiao, Xuebin verfasserin aut Ling, Mo verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 126, Seite 65-71 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:126 pages:65-71 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.21 Messtechnik AR 126 65-71
allfieldsSound	10.1016/j.measurement.2018.05.045 doi (DE-627)ELV000559229 (ELSEVIER)S0263-2241(18)30435-4 DE-627 ger DE-627 rda eng 660 DE-600 50.21 bkl Ye, Xiaoming verfasserin aut The new concepts of measurement error’s regularities and effect characteristics 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In several literatures, the authors give a new thinking of measurement theory system based on error non-classification philosophy, which completely overthrows the existing measurement concept system of precision, trueness and accuracy. In this paper, by focusing on the issues of error’s regularities and effect characteristics, the authors will do a thematic interpretation, and prove that the error’s regularities actually come from different cognitive perspectives, are also unable to be used for classifying errors, and that the error’s effect characteristics actually depend on artificial condition rules of repeated measurement, and are still unable to be used for classifying errors. Thus, from the perspectives of error’s regularities and effect characteristics, the existing error classification philosophy is still incorrect; and an uncertainty concept system, which must be interpreted by the error non-classification philosophy, naturally becomes the only way out of measurement theory. Measurement error Function model Random model Error’s regularities Uncertainty Liu, Haibo verfasserin aut Xiao, Xuebin verfasserin aut Ling, Mo verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 126, Seite 65-71 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:126 pages:65-71 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.21 Messtechnik AR 126 65-71
language	English
source	Enthalten in Measurement 126, Seite 65-71 volume:126 pages:65-71
sourceStr	Enthalten in Measurement 126, Seite 65-71 volume:126 pages:65-71
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topic_facet	Measurement error Function model Random model Error’s regularities Uncertainty
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container_title	Measurement
authorswithroles_txt_mv	Ye, Xiaoming @@aut@@ Liu, Haibo @@aut@@ Xiao, Xuebin @@aut@@ Ling, Mo @@aut@@
publishDateDaySort_date	2018-01-01T00:00:00Z
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author	Ye, Xiaoming
spellingShingle	Ye, Xiaoming ddc 660 bkl 50.21 misc Measurement error misc Function model misc Random model misc Error’s regularities misc Uncertainty The new concepts of measurement error’s regularities and effect characteristics
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topic_title	660 DE-600 50.21 bkl The new concepts of measurement error’s regularities and effect characteristics Measurement error Function model Random model Error’s regularities Uncertainty
topic	ddc 660 bkl 50.21 misc Measurement error misc Function model misc Random model misc Error’s regularities misc Uncertainty
topic_unstemmed	ddc 660 bkl 50.21 misc Measurement error misc Function model misc Random model misc Error’s regularities misc Uncertainty
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title	The new concepts of measurement error’s regularities and effect characteristics
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title_full	The new concepts of measurement error’s regularities and effect characteristics
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title_sort	the new concepts of measurement error’s regularities and effect characteristics
title_auth	The new concepts of measurement error’s regularities and effect characteristics
abstract	In several literatures, the authors give a new thinking of measurement theory system based on error non-classification philosophy, which completely overthrows the existing measurement concept system of precision, trueness and accuracy. In this paper, by focusing on the issues of error’s regularities and effect characteristics, the authors will do a thematic interpretation, and prove that the error’s regularities actually come from different cognitive perspectives, are also unable to be used for classifying errors, and that the error’s effect characteristics actually depend on artificial condition rules of repeated measurement, and are still unable to be used for classifying errors. Thus, from the perspectives of error’s regularities and effect characteristics, the existing error classification philosophy is still incorrect; and an uncertainty concept system, which must be interpreted by the error non-classification philosophy, naturally becomes the only way out of measurement theory.
abstractGer	In several literatures, the authors give a new thinking of measurement theory system based on error non-classification philosophy, which completely overthrows the existing measurement concept system of precision, trueness and accuracy. In this paper, by focusing on the issues of error’s regularities and effect characteristics, the authors will do a thematic interpretation, and prove that the error’s regularities actually come from different cognitive perspectives, are also unable to be used for classifying errors, and that the error’s effect characteristics actually depend on artificial condition rules of repeated measurement, and are still unable to be used for classifying errors. Thus, from the perspectives of error’s regularities and effect characteristics, the existing error classification philosophy is still incorrect; and an uncertainty concept system, which must be interpreted by the error non-classification philosophy, naturally becomes the only way out of measurement theory.
abstract_unstemmed	In several literatures, the authors give a new thinking of measurement theory system based on error non-classification philosophy, which completely overthrows the existing measurement concept system of precision, trueness and accuracy. In this paper, by focusing on the issues of error’s regularities and effect characteristics, the authors will do a thematic interpretation, and prove that the error’s regularities actually come from different cognitive perspectives, are also unable to be used for classifying errors, and that the error’s effect characteristics actually depend on artificial condition rules of repeated measurement, and are still unable to be used for classifying errors. Thus, from the perspectives of error’s regularities and effect characteristics, the existing error classification philosophy is still incorrect; and an uncertainty concept system, which must be interpreted by the error non-classification philosophy, naturally becomes the only way out of measurement theory.
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title_short	The new concepts of measurement error’s regularities and effect characteristics
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author2	Liu, Haibo Xiao, Xuebin Ling, Mo
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doi_str	10.1016/j.measurement.2018.05.045
up_date	2024-07-06T18:22:54.277Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV000559229</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230524153358.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230427s2018 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.measurement.2018.05.045</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV000559229</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0263-2241(18)30435-4</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">660</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">50.21</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Ye, Xiaoming</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">The new concepts of measurement error’s regularities and effect characteristics</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In several literatures, the authors give a new thinking of measurement theory system based on error non-classification philosophy, which completely overthrows the existing measurement concept system of precision, trueness and accuracy. 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Thus, from the perspectives of error’s regularities and effect characteristics, the existing error classification philosophy is still incorrect; and an uncertainty concept system, which must be interpreted by the error non-classification philosophy, naturally becomes the only way out of measurement theory.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Measurement error</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Function model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Random model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Error’s regularities</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Uncertainty</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Liu, Haibo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" 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