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Content provided by Alexander Schacht and Benjamin Piske, biometricians, statisticians and leaders in the pharma industry, Alexander Schacht, Benjamin Piske, and Leaders in the pharma industry. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Alexander Schacht and Benjamin Piske, biometricians, statisticians and leaders in the pharma industry, Alexander Schacht, Benjamin Piske, and Leaders in the pharma industry or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.
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P-value and confidence intervals - the good, the bad, and the ugly

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Manage episode 470737060 series 2400265
Content provided by Alexander Schacht and Benjamin Piske, biometricians, statisticians and leaders in the pharma industry, Alexander Schacht, Benjamin Piske, and Leaders in the pharma industry. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Alexander Schacht and Benjamin Piske, biometricians, statisticians and leaders in the pharma industry, Alexander Schacht, Benjamin Piske, and Leaders in the pharma industry or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.
Interview with Kaspar Rufibach In this episode of The Effective Statistician, I sit down with Kaspar Rufibach to tackle a topic that affects statisticians every day—how to interpret p-values, confidence intervals, and statistical hypotheses. We explore the differences between Fisher’s and Neyman-Pearson’s approaches, clear up common misconceptions, and discuss how misinterpreting statistical significance can lead to flawed conclusions. Using real-world examples from clinical trials and drug development, we highlight best practices for communicating statistical results effectively. Whether you're working with clinicians or business stakeholders, this episode will help you gain clarity on these fundamental statistical concepts and use them correctly in your daily work.
  continue reading

447 episodes

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iconShare
 
Manage episode 470737060 series 2400265
Content provided by Alexander Schacht and Benjamin Piske, biometricians, statisticians and leaders in the pharma industry, Alexander Schacht, Benjamin Piske, and Leaders in the pharma industry. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Alexander Schacht and Benjamin Piske, biometricians, statisticians and leaders in the pharma industry, Alexander Schacht, Benjamin Piske, and Leaders in the pharma industry or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.
Interview with Kaspar Rufibach In this episode of The Effective Statistician, I sit down with Kaspar Rufibach to tackle a topic that affects statisticians every day—how to interpret p-values, confidence intervals, and statistical hypotheses. We explore the differences between Fisher’s and Neyman-Pearson’s approaches, clear up common misconceptions, and discuss how misinterpreting statistical significance can lead to flawed conclusions. Using real-world examples from clinical trials and drug development, we highlight best practices for communicating statistical results effectively. Whether you're working with clinicians or business stakeholders, this episode will help you gain clarity on these fundamental statistical concepts and use them correctly in your daily work.
  continue reading

447 episodes

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