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== 2022 Lectures ==
 
== 2022 Lectures ==
  
=== Week 1 ===
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==== Week 1 ===
  
 
[[Media:Al-Marzouki_s05.pdf|Al-Marzouki]] - The effect of scientific misconduct on the results of clinical trials: A Delphi survey
 
[[Media:Al-Marzouki_s05.pdf|Al-Marzouki]] - The effect of scientific misconduct on the results of clinical trials: A Delphi survey
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[[Media: Moving_to_a_World_Beyond_p_0_05.pdf|Moving to a World beyond]] - Moving to a World Beyond “p < 0.05”
 
[[Media: Moving_to_a_World_Beyond_p_0_05.pdf|Moving to a World beyond]] - Moving to a World Beyond “p < 0.05”
  
On Being A Scientist: Responsible Conduct for Research in Science (RCRS) -- Dr. Bhramar Mukherjee
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=== On Being A Scientist: Responsible Conduct for Research in Science (RCRS) -- Dr. Bhramar Mukherjee===
 
*[[Media:On_being_scientist_2009.pdf|On Being A Scientist Article]]
 
*[[Media:On_being_scientist_2009.pdf|On Being A Scientist Article]]
 
*[[Media:On+Being+A+Scientist.pptx| Slides]]
 
*[[Media:On+Being+A+Scientist.pptx| Slides]]

Revision as of 15:07, 13 July 2022

2022 Lectures

= Week 1

Al-Marzouki - The effect of scientific misconduct on the results of clinical trials: A Delphi survey Baggerly Coombes - Deriving Chemosensitivity from cell lines: forensic bioinformatics and reproducible research in high-throughput biology Benjamini - Redefine statistical significance Ethical guidelines - Ethical Guidelines for Statistical Practice article Ethics reviews - Ethical statistical practice review slides Moving to a World beyond - Moving to a World Beyond “p < 0.05”

On Being A Scientist: Responsible Conduct for Research in Science (RCRS) -- Dr. Bhramar Mukherjee

Cluster Computing -- Dan Barker

  -[Cluster Computing Slides]
  -Recording
  • Study Design and Inference -- Dr. Rodrick Little
  -Recording
  • Observational Data, Bias -- Dr. Rodrick Little
  -Recording
  • Probability Review -- Soumik Purkayastha
  -Slides
  -Handout
  -Recording
  • Parameter Estimation & Likelihood -- Dr. Rodrick Little
  • Causal Inference -- Dr. Walter Dempsey
  -Recording
  • Linear Regression Review -- Soumik Purkayastha
  -Slides
  -Handout
  -Recording
  • Data Wrangling in R -- Mike Kleinsasser
  -Recording Part I
  -Recording Part II
  • Linear Algebra Review -- Rupam Bhattacharyya
  -Recording
  • Visualizing Data in R with ggplot2 -- Erin Hodgess
  • Journey Lecture -- Dr. Jeremy Taylor
  -Recording

Week 2

  • Python Parts I & II -- Dr. Fred Feng
  -Recording Part I
  -Recording Part II
  • Generalized Linear Models Review -- Jon Boss
  -Recording
  • Python Parts III & IV -- Dr. Fred Feng
  • Logistic Regression Review -- Elizabeth Chase
  • Machine Learning -- Dr. Maggie Makar
  • R Markdown -- Dr. Phil Boonstra
  • Prediction Analysis -- Dr. Phil Boonstra
  • Correlated Data Models -- Irena Chen
  • Unsupervised Learning & Clustering -- Dr. Somayeh Molaei
  • Journey Lecture -- Dr. Jean Morrison