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Podcasts on statistics in cardiovascular science: Part I

Statistical Principles in Basic Cardiovascular Research - Introduction

The Scientists of Tomorrow present a series of 3 podcasts on statistics in cardiovascular science. Part I is presented below while Parts II and III will be included in the upcoming articles of the Scientists of Tomorrow.

Statistics is always a challenge for the young basic or clinical researcher. How many times has a PhD student working in the field of Cardiovascular Sciences asked for help from a statistician? Usually this extra help comes at the very end of their PhD project, when the paper is almost ready for submission, and of course then it’s too late to go back to the lab and do more experiments, or randomize treatments in a blinded way.

Usually the young researcher relies in the statistical expertise of a post-doc, which may not always be correct. So it’s important for young researchers to understand the basic principles of statistics before they even design their first experiments, so that their study design would allow them to draw safe conclusions. Is randomization important in basic science? Is blinding in data collection and analysis an issue that needs to be addressed?  When the results are available, how should the data be explored and analyzed? When should a statistician be consulted?

Basic Sciences, Pharmacology, Genomics and Cardiovascular Pathology


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This first podcast (below)includes an interview of Prof. Sir Rory Collins, Professor of Medicine & Epidemiology and Head of the clinical trials service unit in the University of Oxford by Prof. Charis Antoniades, Associate Professor of Cardiovascular Medicine in the University of Oxford, on behalf of the SoT.

Conclusion:

Professor Sir Collins is one of the legends of modern Cardiovascular Medicine, and his large-scale clinical trials have changed clinical practice in Cardiology many times so far. In this podcast he introduces us to the fundamental principles of statistics and their importance in basic science. He discusses the importance of blinding, randomization, statistical power, exploring the data and choosing the right statistical test.

Enjoy viewing this podcast and don’t miss the next two podcasts.