Mathematics and Statistics in Anaesthesia

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Brand: OUP Oxford

ISBN: 9780192623126

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Description

Anaesthetic trainees often have enormous trouble understanding the quantitative aspects of the basic sciences underlying clinical anaesthetic practice. The subjects of pharmokinetics and statistics are often unpopular with trainees, and studied with little enthusiasm. In spite of their reluctance, this is an area that they are required to study and understand as a core part of their training for postgraduate exams. Mathematics and statistics for anaesthetists presentssimple mathematical ideas, and explains how these can be used to model and understand problems which arise in clinical anaesthesia. The common features of the underlying mathematics are emphasised through a pictorial/graphical approach, in preference to vast amounts of algebra. The book presents statistics in aninformal and less intimidating style that most standard statistical texts, incorporating illustrations and cartoons throughout. The book will be valuable to anaesthetists, in guiding them through what can be an intimidating part of their training.

Product Details

Brand OUP Oxford

Reference 84619

EAN13 9780192623126

ISBN 9780192623126

Data sheet

Publication date: 1998
Issue number: 1
Cover: paperback
Pages count: 268
Dimensions (mm): 189 x 246
Weight (g): 528

Section 1 Physiological and pharmacological modelling; Introduction; The input-output principle; Steady-states:: Alveolar ventillation & PaCO2; Gas laws; Flux & the Fick principle; Fick & cardiac output; dilution methods; Fick & cerebral blood flow; Apnoeic oxygenation; Nitrogen washout and preoxygeneration; Time constants; Step change in ventilation; Air embolism; Pharmacokinetic models; Drug-receptor interaction; Drug antagonism; Oscillating systems; Damped oscillations; Forced oscillation; Modelling arterial pressure waves; Section 2 - Mathematical background; Numbers; Functions; Pattern functions & transformation; Constant function; Linear; Rectangular hyperbolic functions; Polynomial functions; Inverse functions; Exponential & logarithmic functions; Sinusoidal functions; Functions of more than one variable; The derivative & differentiation; Maxima & minima; Integration; Differential equations; Numerical methods for differential equations; Section 3 - Probability & statistics; Probability models and simulation; Waiting times in a Poisson process; Passing the fellowship; the binomial distribution; Measuring SVP; the normal distribution; Modelling with random variables; Sums of random variables; Probability; Conditional probability & Bayes theorem; Summary measures; location and dispersion; The normal distribution; Statistical inference; Sample mean. Estimation & confidence; Sample variance; Significance testing; Samples of unknown mean and variance; Categorial data; Related variables; linear regression; Related variables; correlation; Distribution-free methods; Stochastic IOP. Queues; Bibliography; Index;