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Calibration: A procedure which enables a series of simply obtainable but inaccurate measurements of some quantity of interest to be used to provide more precise estimates of the required values. Assume, for instance, there is a well-established, accurate process of measuring the concentration of a given chemical compound, but that it is too expensive and cumbersome for routine use. A cheap and simple to apply an alternative is developed that is, though, known to be imprecise and possibly subject to bias. By using both methods or ways over a range of concentrations of compound, and applying regression analysis to the values from the cheap way and the corresponding values from accurate method, a calibration curve can be constructed which may, in future applications, be used to read off the estimates of the needed concentration from the values given by less involved, inaccurate procedure.
Principal factor analysis is the method of factor analysis which is basically equivalent to a principal components analysis performed on reduced covariance matrix attained by repl
Outliers - Reasons for Screening Data Outliers are due to data entry errors, subject is not a member of the population that the sample is trying to represent, or the subject i
need answers to questions in book advanced and multivariate statistical methods
R-squared is regarded as the coefficient of determination and is used to give the proportion of the fluctuation of the variance of one variable to another variable. R-squared also
Quasi-experiment is a term taken in use for studies which resemble experiments but are weak on some of the characteristics, particularly that allocation of the subjects to groups
Ignorability : The missing data mechanism is said to be ignorable for likelihood inference if (1) the joint likelihood for the responses of the interest and missing data indicators
The term which is used in the industrial experimentation, where there is commonly a large set of candidate factors believed to have the possible significant influence on the respon
Balanced incomplete block design : A design in which all the treatments are not used in all blocks. Such designs have the below stated properties: * each block comprises the
PRINCIPLES OF MODELLING IN OR.
Conditional logistic regression : The form of logistic regression designed to work with the clustered data, such as data including matched pairs of the subjects, in which subject-s
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