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Contents
- 1 2022 Lectures
- 1.1 Week 1
- 1.1.1 On Being A Scientist: Responsible Conduct for Research in Science (RCRS) - Dr. Bhramar Mukherjee
- 1.1.2 Cluster Computing - Dan Barker
- 1.1.3 Study Design and Inference - Dr. Rodrick Little
- 1.1.4 Observational Data and Bias - Dr. Rodrick Little
- 1.1.5 Probability Review - Soumik Purkayastha
- 1.1.6 Parameter Estimation & Likelihood - Dr. Rodrick Little
- 1.1.7 Causal Inference - Dr. Walter Dempsey
- 1.1.8 Linear Regression Review - Soumik Purkayastha
- 1.1.9 Data Wrangling in R - Mike Kleinsasser
- 1.1.10 Linear Algebra Review - Rupam Bhattacharyya
- 1.1.11 Visualizing Data in R with ggplot2 - Erin Hodgess
- 1.1.12 Journey Lecture - Dr. Jeremy Taylor
- 1.2 Week 2
- 1.2.1 Python Parts I & II - Dr. Fred Feng
- 1.2.2 Generalized Linear Models Review - Jon Boss
- 1.2.3 Python Parts III & IV - Dr. Fred Feng
- 1.2.4 Logistic Regression Review - Elizabeth Chase
- 1.2.5 Machine Learning -- Dr. Maggie Makar
- 1.2.6 R Markdown - Dr. Phil Boonstra
- 1.2.7 Prediction Analysis - Dr. Phil Boonstra
- 1.2.8 Correlated Data Models - Irena Chen=
- 1.2.9 Unsupervised Learning & Clustering - Dr. Somayeh Molaei
- 1.2.10 Journey Lecture - Dr. Jean Morrison
- 1.1 Week 1
2022 Lectures
Week 1
On Being A Scientist: Responsible Conduct for Research in Science (RCRS) - Dr. Bhramar Mukherjee
- 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 Article
- Slides
- Recording
Cluster Computing - Dan Barker
- [Cluster Computing Slides]
- Recording
Study Design and Inference - Dr. Rodrick Little
Observational Data and Bias - Dr. Rodrick Little
Probability Review - Soumik Purkayastha
Parameter Estimation & Likelihood - Dr. Rodrick Little
Causal Inference - Dr. Walter Dempsey
Linear Regression Review - Soumik Purkayastha
Data Wrangling in R - Mike Kleinsasser
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
