Lecturers:
Stuart Brown (Stuart.Brown@nyumc.org)
David Fenyö (David@FenyoLab.org)
Huilin Li (Huilin.Li@nyumc.org)

Tutorial Instructors:
Pamela Wu (Pamela.Wu@nyumc.org)
Amanda Ernlund (Amanda.Ernlund@nyumc.org)
Xuya Wang (Xuya.Wang@nyumc.org)

Course Overview

The goal for the Introduction to Biostatistics and Bioinformatics course is to provide an introduction to statistics and informatics methods for the analysis of data generated in biomedical research. Practical examples covering both small-scale lab experiments and high-throughput assays will be explored. The course covers a wide range of topics in a short time so the focus will be on the basic concepts, and in the practical programming exercises the students explore these basic concept and common pitfalls. An introduction of basic Python and R programming will be given throughout the course and many exercises will involve programming.

Learning objectives

The student will be introduced to entry-level methods in the biostatistics and bioinformatics.

Course Assessment

• Readings and participation (20%): Students are required to attend class, to complete reading assignments and to participate in discussions and engage in healthy exchange of ideas.
• Assignments (40%): Programming assignment will be given at the end of each class, and the solutions to these assignments should be e-mailed to Assignments@FenyoLab.org within a week.
• Exam (40%): There will be one exam in this class and it will cover the entire course material.

Make-up examinations (for final only) will be given under special circumstances. Documentation will be required to verify a student’s claim. If a make-up exam is permitted, a different exam will be written for that student and may have a different format than the regular examination.

The assignments must be turned in on time and no late assignments will be accepted.

If there is a time that you believe that there is a mistake in grading of an assignment/exam, you will have a chance to appeal your exam grade within a week after you receive your grade. If you think this is the case, you must write a note describing the error, attach it to the original exam, and give it to me within a week of the return of your exam. I will review your argument and my initial grading, and then return your exam with a decision to you in a timely manner.

General Policies

• Late/missed work: You must adhere to the due dates for all required submissions. If you miss a deadline, then you will not get credit for that assignment/post. Try to avoid last minute submissions.
• Incompletes: No “Incompletes” will be assigned for this course unless we are at the very end of the course and you have an emergency.
• Responding to Messages: I will check e-mails daily during the week, and I will respond to course related questions within 48 hours.
• Announcements: I will make announcements throughout the semester by e-mail. Make sure that your email address is updated; otherwise you may miss important emails from me.
• Safeguards: Always back up your work on a safe place (electronic file with a backup is recommended) and make a hard copy. Do not wait for the last minute to do your work. Allow time for deadlines.
• Plagiarism: Plagiarism, the presentation of someone else's words or ideas as your own, is a serious offence and will not be tolerated in this class. The first time you plagiarize someone else's work, you will receive a zero for that assignment. The second time you plagiarize, you will fail the course with a notation of academic dishonesty on your official record.

Python for Biologists: A complete programming course for beginners by Martin Jones

The Cartoon Guide to Statistics by Larry Gonick

Think Stats by Allen B. Downey

Lectures

Lecture 1 Pre-test (August 20, 2015 Smilow 1st Floor Seminar Room 1pm)


Lecture 2 Introduction to Biological Data (September 1, 2015 Skirball 3rd Floor Seminar Room 2pm)
Lecturer: Brown ( Video , Slides )
Homework (due date: September 6)