Download Cracking the Intercollegiate General Surgery FRCS Viva: A by Elizabeth Ball, Stewart Walsh, Tjun Tang PDF

By Elizabeth Ball, Stewart Walsh, Tjun Tang

The FRCS exam is the final hurdle at the highway to self sustaining perform as a specialist doctor within the uk and eire. The voce viva element of the examination might be quite demanding for applicants who needs to reveal not just their wisdom of varied surgical subject matters, but additionally their reasoning and decision-making abilities.

Cracking the Intercollegiate common surgical procedure FRCS Viva: A Revision advisor provides the framework and data to move the non-subspecialty sections of the FRCS (General surgical procedure) viva and scientific exam. This accomplished revision textual content covers all crucial issues in severe care, emergency and basic surgical procedure in addition to serious appraisal of study papers, easy statistics and information manipulation for the tutorial part.

Highlights:

  • Layout: a special procedure recreates the constitution and content material of every person viva

  • Past questions: real viva questions pooled from winning FRCS applicants are integrated so that you understand what worked

  • Contributors: perception from skilled clinicians who've informed within the united kingdom larger surgical education system

This crucial revision consultant will give you the important issues for every subject, offered in a concise, dependent demeanour and referenced the place acceptable. it's crucial interpreting for an individual getting ready for the FRCS basic surgical procedure exam.

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Additional resources for Cracking the Intercollegiate General Surgery FRCS Viva: A Revision Guide

Sample text

They also tend to rely on ranking the values in the data set rather than using the actual data. What tests should be used for categorical, non-normal and normal data? 1. 1 Statistical Tests Used to Analyse a Given Data Set Categorical One sample Chi2 Two groups, unpaired Two groups, paired Chi2 (unpaired) McNemar’s test More than two groups, unpaired Chi2 More than two groups, paired McNemar’s test Non-normal Compare median Normal Compare mean Wilcoxon’s signed rank test Mann–Whitney Wilcoxon’s matched pairs Kruskall–Wallis ANOVA Friedman’s test One-sample t-test t-Test t-Test ANOVA ANOVA POWER What do you understand by the term ‘power’ in medical studies?

In the example of the blue-eyed and brown-eyed men, a type 1 error would involve a conclusion that eye colour did influence AAA risk when, in fact, no such relationship exists. • In simple terms, a type 1 error occurs when we fail to recognise a falsehood. • The rate of type 1 errors usually equals the significance level of the test. • At the 5% significance level, the investigator accepts that 1 in 20 tests will result in an erroneous rejection of the null hypothesis. What is meant by a type 2 error?

It should have a well-constructed, relevant, clinical question, ideally expressed in PICO terms: population, intervention, controls and outcomes. • Objective inclusion and exclusion criteria should be defined at the outset. • The key outcomes should also be explicitly defined in the review protocol. • The review should use a structured search strategy in order to identify all relevant studies, ideally both published and unpublished. • Where necessary, efforts should be made to obtain missing but relevant data from published papers, to avoid propagating publication bias.

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