Difference between revisions of "BCH2024-2012"
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| − | * [http://biochemistry.utoronto.ca/steipe/abc/CourseMaterials/ | + | * [http://biochemistry.utoronto.ca/steipe/abc/CourseMaterials/R_Module_4_Regression.pdf Module 4 - Regression (PDF, 1.9 MB)] |
| + | * [http://biochemistry.utoronto.ca/steipe/abc/CourseMaterials/R_Module_5_HypothesisTesting.pdf Module 5 - Hypothesis Testing (PDF, 2.2 MB)] | ||
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* ... [http://biochemistry.utoronto.ca/steipe/abc/CourseMaterials/Module_4_Regression.R Module 4 (Regression)] | * ... [http://biochemistry.utoronto.ca/steipe/abc/CourseMaterials/Module_4_Regression.R Module 4 (Regression)] | ||
* ... [http://biochemistry.utoronto.ca/steipe/abc/CourseMaterials/Module_5_HypothesisTesting.R Module 5 (Hypothesis Testing)] | * ... [http://biochemistry.utoronto.ca/steipe/abc/CourseMaterials/Module_5_HypothesisTesting.R Module 5 (Hypothesis Testing)] | ||
| + | * ... [http://biochemistry.utoronto.ca/steipe/abc/CourseMaterials/Module_6_PCA.R Module 6 (Principal Component Analysis)] | ||
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Data sets: | Data sets: | ||
Latest revision as of 18:15, 30 August 2012
Exploratory Data Analysis using R
This is the 2012 BCH2024 course on Exploratory data analysis using R taught by Boris Steipe at the University of Toronto.
Contents
Organization
All sessions will take place in MSB 3290.
Meeting times are:
- Thursday, Aug. 23 14:00-16:00
- Friday, Aug. 24 14:00-16:00
- Tuesday, Aug. 28 10:00-12:00
- Thursday, Aug. 30 14:00-16:00
In addition to the course sessions, there are a number of lab modules for you to work through at home.
Auditors are welcome IF they commit to participating actively in all sessions.
Grading will be 50% course participation and 50% mini project.
Course participation is:
- Being prepared for and actively participating in class.
- Contributing to e-mail discussion of questions arising from the course material or the lab modules.
The mini project comprises:
- Search for an R package that implements an analysis relevant to EDA in the scope your thesis project. Alternatively you can come up with a creative, interesting use of the default R functionality in script form, or as a function that you write.
- Summarize what you plan to do, eMail me your proposal and have me sign off on the suitability of the proposal.
- Develop a script that guides a user through installation of the package (or defines your function) and executes a typical use case. Don't forget to include a sample dataset. Make sure your script is extensively annotated with comments and that you include notes on the interpretation of results.
- Submit your script and sample data to me no later than Friday morning, Aug. 31.
Links and Material
- The course R tutorial
Lecture slides
R scripts for ...
- ... Module 1 (Landscape)
- ... Module 2 and 3 (EDA, Plotting)
- ... Module 4 (Regression)
- ... Module 5 (Hypothesis Testing)
- ... Module 6 (Principal Component Analysis)
Data sets:
