Biol20N02 2016: Difference between revisions

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==Course Outline==
==Course Outline==
===Week 1. Introduction & tutorials for R/R studio===
===Feb 2. Introduction & tutorials for R/R studio===
===Week 2. Statistics & samples===
===Feb 9. No class (Friday Schedule)===
===Week 3. Displaying data===
===Feb 16. Introduction & tutorials for R/R studio===
===Week 4. Describing data; Exam 1.===
==-Feb 23. Statistics & samples===
===Week 5. Probability and hypothesis testing===
===March 1. Displaying data===
===Week 6. Analysis of proportions===
===March 8. Describing data; Exam 1.===
===Week 7. Analysis of frequencies===
===March 15. Probability and hypothesis testing===
===Week 8. Contingency tests; Exam 2===
===March 22. Analysis of proportions===
===Week 9. Normal distribution and controls===
===March 29. Analysis of frequencies===
===Week 10. Comparing two means===
===April 5. Contingency tests; Exam 2===
===Week 11. Designing experiments===
===April 12. Normal distribution and controls===
===Week 12. Comparing more than two groups; Exam 3===
===April 19. Comparing two means===
===Week 13. Correlation analysis===
===April 26. No Class (Spring break)===
===Week 14. Regression analysis===
===May 3. Designing experiments===
===Week 15. Review and Exam 4 (final comprehensive exam)===
===May 10. Comparing more than two groups; Exam 3===
===May 17. Correlation analysis===
===May 24. Final Exam (Comprehensive)===
===May 31. Grades submitted to Registrar Office===

Revision as of 20:54, 25 January 2016

Analysis of Biological Data (BIOL 20N02, Spring 2015)
Instructor: Dr Weigang Qiu, Associate Professor, Department of Biological Sciences
Room: 1001B HN (North Building, 10th Floor, Mac Computer Lab)
Hours: Tuesdays 10-1
Office Hours: Belfer Research Building (Google Map) BB-402; Wed 5-7 pm or by appointment
Course Website: http://diverge.hunter.cuny.edu/labwiki/Biol20N2_2016

Course Description

With rapid accumulation of genome sequences and digitalized health data, biomedicine is becoming a data-intensive science. This course is a hands-on, computer-based workshop on how to visualize and analyze large quantities of biological data. The course introduces R, a modern statistical computing language and platform. Students will learn to use R to make scatter plots, bar plots, box plots, and other commonly used data-visualization techniques. The course will review statistical methods including hypothesis testing, analysis of frequencies, and correlation analysis. Student will apply these methods to the analysis of genomic and health data such as whole-genome gene expressions and SNP (single-nucleotide polymorphism) frequencies.

This 3-credit experimental course fulfills elective requirements for Biology Major I. Hunter pre-requisites are BIOL100, BIOL102 and STAT113.

Textbooks

Course Outline

Feb 2. Introduction & tutorials for R/R studio

Feb 9. No class (Friday Schedule)

Feb 16. Introduction & tutorials for R/R studio

-Feb 23. Statistics & samples=

March 1. Displaying data

March 8. Describing data; Exam 1.

March 15. Probability and hypothesis testing

March 22. Analysis of proportions

March 29. Analysis of frequencies

April 5. Contingency tests; Exam 2

April 12. Normal distribution and controls

April 19. Comparing two means

April 26. No Class (Spring break)

May 3. Designing experiments

May 10. Comparing more than two groups; Exam 3

May 17. Correlation analysis

May 24. Final Exam (Comprehensive)

May 31. Grades submitted to Registrar Office

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