USMLE Pro vs Bayesian P

Advanced USMLE preparation with a clinical centre of gravity: 2000+ advanced-level questions for Step 2 CK and Step 3, high-yield flashcards, Step-specific learning paths, and analytics that find your gaps. Step 1 content is included, and all of it works offline. THE QUESTION BANK 2000+ advanced-level exam-style questions across Step 1, Step 2 CK and Step 3, each with a detailed explanation that reinforces the underlying concept and shows why the other options do not hold. FLASHCARDS High-yield flashcards to reinforce the core concepts — the facts you need to produce instantly rather than reason towards. LEARNING PATHS Step-specific paths so you are working through the material in an order that matches the exam you are actually sitting, instead of assembling a plan yourself. ANALYTICS Smart performance tracking that highlights weak areas, so your time goes where it will change your score. OFFLINE Questions and flashcards download for offline study — built for travel, clinical rotations and hospital dead zones. ALL THREE STEPS COVERED Step 1 — basic sciences, pathology, pharmacology, microbiology, immunology, physiology Step 2 CK — clinical knowledge, patient care, diagnosis, medicine, surgery, paediatrics, obstetrics and gynaecology, psychiatry Step 3 — case scenarios, advanced clinical decision making, biostatistics, medical ethics WHO IT IS FOR Students and graduates preparing for USMLE Step 2 CK, residents sitting Step 3, and international medical graduates working towards US certification and the residency match. It works just as well for other medical licensing exams such as COMLEX. FEEDBACK We keep improving this and your mail matters: info@testflood.com DISCLAIMER This app is not affiliated with, endorsed by, or connected to the USMLE, NBME or FSMB. It is an independent study aid for educational use.

Calculate probability of outcomes of clinical trials, by interpreting reported p-values in the context of scientific expectations, using prior probabilities of outcomes and Bayesian thinking. · p-values are frequently misused and misinterpreted ( see American Statistical Association statement on p-values) · Bayesian inference aids interpretation of p-values with reference to prior knowledge of the probability of the experimental outcome · P-value Interpreter permits realistic interpretation of reported p-values from user entered pre-trial probabilities of clinical trial outcomes and p-values for single and sequential trials · "Learn more" buttons lead to explanations of prior probabilities, p-values and Bayesian probabilities employed in calculating the direct probability of the trial outcomes (e.g. null hypothesis being false), illustrated with examples