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Modelling mark-recapture data is trending towards a more integrative approach, [23] which combines mark-recapture data with population dynamics models and other types of data. The integrated approach is more computationally demanding, but extracts more information from the data improving parameter and uncertainty estimates.
By convention, negative integers are written with a bar, as in 3 for −3. The integers are usually written in lowest terms, i.e. their greatest common divisor should be 1. Miller indices are also used to designate reflections in X-ray crystallography.
This article is a list of standard proofreader's marks used to indicate and correct problems in a text. Marks come in two varieties, abbreviations and abstract symbols. Marks come in two varieties, abbreviations and abstract symbols.
A health utility value of 1.00 indicates perfect health while a score of 0.00 indicates death. Negative values account for the fact that some health states are identified by the general public as being worse than death. To calculate a health utility score, health states for each response are converted using a look-up table and mathematical formula.
The Lincoln index is a statistical measure used in several fields to estimate the population size of an animal species. Described by Frederick Charles Lincoln in 1930, it is also sometimes known as the Lincoln-Petersen method after C.G. Johannes Petersen who was the first to use the related mark and recapture method.
The degree of differentiation shown in marks varies greatly from country to country and in many cases within a single country or institution. Expression in terms of ECTS grades is simple where the local marks are highly differentiated (i.e., the local grading scale has as much or more possible values than the ECTS scale).
Grading in education is the application of standardized measurements to evaluate different levels of student achievement in a course. Grades can be expressed as letters (usually A to F), as a range (for example, 1 to 6), percentages, or as numbers out of a possible total (often out of 100).
NRI attempts to quantify how well a new model correctly reclassifies subjects. Typically this comparison is between an original model (e.g. hip fractures as a function age and sex) and a new model which is the original model plus one additional component (e.g. hip fractures as a function of age, sex, and a genetic or proteomic biomarker).