Thermodynamics as a theory of measurement

2022 ◽  
Vol 172 ◽  
pp. 104430
Author(s):  
Valentin Lychagin
Keyword(s):  
Theory Of Measurement

Theory of Measurement

1971 ◽  
Author(s):  
Johann Pfanzagl
Keyword(s):  
Theory Of Measurement

The Axioms of Quantity and the Theory of Measurement

1996 ◽  
Vol 40 (3) ◽  
pp. 235-252 ◽  
Author(s):  
Joel Michell ◽  
Catherine Ernst
Keyword(s):  
Theory Of Measurement

Quantum theory of measurement and ergodicity conditions

1962 ◽  
Vol 33 ◽  
pp. 297-319 ◽  
Author(s):  
A. Daneri ◽  
A. Loinger ◽  
G.M. Prosperi
Keyword(s):  
Quantum Theory ◽  
Theory Of Measurement ◽  
Quantum Theory Of Measurement

Chapter 1: Toward a Theory of Measurement and Appraisal in Education

1963 ◽  
Vol 146 (1) ◽  
pp. 3-13
Author(s):  
Gene D. Phillips
Keyword(s):  
Theory Of Measurement

Utility of Analysis of Variance with Repeated Measures Programs for Estimating Reliability

1975 ◽  
Vol 41 (2) ◽  
pp. 441-442 ◽  
Author(s):  
Ronald A. Berk
Keyword(s):  
Measurement Error ◽  
Computer Program ◽  
Analysis Of Variance ◽  
Repeated Measures ◽  
Theory Of Measurement ◽  
Generalizability Theory ◽  
Intraclass Correlation ◽  
Program Output

This paper presents a brief description of the generalizability theory of measurement error and its relation to analysis of variance with repeated measures. The intraclass correlation is defined in terms of analysis of variance computer program output. The usefulness of several programs is discussed.

Mathematical Alternatives to Standard Probability that Provide Selectable Degrees of Precision

2017 ◽  
Author(s):  
Terrence Fine
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Models ◽  
Theory Of Measurement ◽  
Belief Functions ◽  
Standard Practice ◽  
Mathematical Probability ◽  
Comparative Probability ◽  
The Relationship ◽  
Standard Probability

This chapter challenges the nearly universal reliance upon standard mathematical probability for mathematical modeling of chance and uncertain phenomena, and offers four alternatives. In standard practice, precise assignments are made inappropriately, even to the occurrences of events that may be unobservable in principle. Four familiar examples of chance or uncertain phenomena are discussed, about which this is true. The theory of measurement provides an understanding of the relationship between the accuracy of information and the precision with which the phenomenon under examination should be modeled mathematically. The model of modal or classificatory probability offers the least precision. Comparative probability, plausibility/belief functions and upper/lower probabilities are carefully considered. The selectable precision of these alternative mathematical models of chance and uncertainty makes for an improved range of levels of accuracy in modeling the empirical domain phenomena of chance, uncertainty, and indeterminacy. Knowledge of such models encourages further thought in this direction.

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