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*[[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]] | ||
| − | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=6627a5d1-b57c-4338-a11a-aeba012b3492 | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=6627a5d1-b57c-4338-a11a-aeba012b3492 Recording] |
====Cluster Computing - Dan Barker==== | ====Cluster Computing - Dan Barker==== | ||
*[Cluster Computing Slides] | *[Cluster Computing Slides] | ||
| − | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=e450567f-0720-4154-9624-aeba014a4f0d | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=e450567f-0720-4154-9624-aeba014a4f0d Recording] |
====Study Design and Inference - Dr. Rod Little==== | ====Study Design and Inference - Dr. Rod Little==== | ||
| − | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=c011d778-b801-4a7b-8f2d-aebb00d6e95a | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=c011d778-b801-4a7b-8f2d-aebb00d6e95a Recording] |
====Parameter Estimation and Likelihood - Dr. Rodrick Little==== | ====Parameter Estimation and Likelihood - Dr. Rodrick Little==== | ||
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*[https://rpubs.com/soumikp/bdsi2022ProbSlides Slides] | *[https://rpubs.com/soumikp/bdsi2022ProbSlides Slides] | ||
*[https://rpubs.com/soumikp/bdsi2022ProbHandout Handout] | *[https://rpubs.com/soumikp/bdsi2022ProbHandout Handout] | ||
| − | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=57e7a634-7808-4225-980a-aebb0120c3c3 | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=57e7a634-7808-4225-980a-aebb0120c3c3 Recording] |
====Observational Data and Bias - Dr. Rod Little==== | ====Observational Data and Bias - Dr. Rod Little==== | ||
| − | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=3d3fdabc-9342-4b93-816a-aebb00f4096f | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=3d3fdabc-9342-4b93-816a-aebb00f4096f Recording] |
====Causal Inference - Dr. Walter Dempsey==== | ====Causal Inference - Dr. Walter Dempsey==== | ||
| − | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=a1f612be-5d90-4b2c-b3cc-aebc00f3f0e3 | + | *[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=a1f612be-5d90-4b2c-b3cc-aebc00f3f0e3 Recording] |
====Linear Regression Review - Soumik Purkayastha==== | ====Linear Regression Review - Soumik Purkayastha==== | ||
Revision as of 15:28, 13 July 2022
Contents
- 1 2022 Lectures
- 1.1 Week 1
- 1.1.1 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. Rod Little
- 1.1.4 Parameter Estimation and Likelihood - Dr. Rodrick Little
- 1.1.5 Probability Review - Soumik Purkayastha
- 1.1.6 Observational Data and Bias - Dr. Rod 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 - Dr. 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 Review - Irena Chen=
- 1.2.9 Unsupervised Learning and Clustering - Dr. Somayeh Molaei
- 1.2.10 Journey Lecture - Dr. Jean Morrison
- 1.3 Week 3
- 1.3.1 Data Mining - Dr. Somayeh Molaei
- 1.3.2 Scientific Writing - Dr. Brett Griffiths
- 1.3.3 Pick Me! - Dr. Brett Griffiths
- 1.3.4 Model Selection - Yichen Si
- 1.3.5 Visualization Workshop - Diamond Buchanan
- 1.3.6 Health Data Science Concentration Presentation - Dr. Hui Jiang
- 1.3.7 Journey Lecture - Pedro Orozco del Pino
- 1.4 Week 4
- 1.4.1 Genetics and Genomics - Dr. Jean Morrison
- 1.4.2 Spatial Epidemiology - Dr. Jon Zelner
- 1.4.3 Intro to Bayes - Dr. William Wen
- 1.4.4 Stroke Disparities - Dr. Lynda Lisabeth
- 1.4.5 Personalized Medicine - Dr. Lars Fritsche
- 1.4.6 Missing Data - Dr. Peisong Han
- 1.4.7 Bioinformatics and Epidemiology Career Roundtable - Dr. Maureen Sartor
- 1.4.8 Human Centered Computing - Dr. Nikola Banovic
- 1.5 Week 5
- 1.5.1 Deep Learning - Dr. Jian Kang
- 1.5.2 Optimization - Dr. Jian Kang
- 1.5.3 Natural Language Processing - Dr. Karandeep Singh
- 1.5.4 Radiation Oncology - Dr. Arvind Rao
- 1.5.5 Clinical Trials - Dr. Kelley Kidwell
- 1.5.6 Electronic Health Records - Dr. Sachin Kheterpal
- 1.5.7 Precision Health for Diverse Populations - Dr. Jennifer Smith
- 1.5.8 Better, Not Just Bigger, Data Analytics - Dr. Brahmajee Nallamothu
- 1.5.9 Policy and Machine Learning - Dr. Rahul Ladania
- 1.5.10 Journey Lecture - Dr. Snigdha Panigrahi
- 1.6 Week 6
- 1.7 Research Symposium
- 1.8 Professional Development Day
- 1.1 Week 1
2022 Lectures
Week 1
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. Rod Little
Parameter Estimation and Likelihood - Dr. Rodrick Little
Probability Review - Soumik Purkayastha
Observational Data and Bias - Dr. Rod Little
Causal Inference - Dr. Walter Dempsey
Linear Regression Review - Soumik Purkayastha
Data Wrangling in R - Mike Kleinsasser
Linear Algebra Review - Rupam Bhattacharyya
Visualizing Data in R with ggplot2 - Dr. Erin Hodgess
Journey Lecture - Dr. Jeremy Taylor
Week 2
Python Parts I & II - Dr. Fred Feng
Generalized Linear Models Review - Jon Boss
Python Parts III & IV - Dr. Fred Feng
Logistic Regression Review - Elizabeth Chase
Machine Learning - Dr. Maggie Makar
R Markdown - Dr. Phil Boonstra
- [ Recording]
