Course Information

Description

This course provides a survey of regression techniques for outcomes common in public health data including continuous, binary, count and survival data. Emphasis is on developing a conceptual understanding of the application of these techniques to solving problems, rather than to the numerical details. Extensive use of the computer will be made for analysis of datasets.

This course is designed for graduate and advanced undergraduate students who will be analyzing data with scientific colleagues and who want to develop a practical hands-on toolkit and gain experience in distilling complex statistical information into formats understandable to colleagues. This course will feature R programming elements. To make the most of R students will be expected to use RStudio. There are videos on the course’s R page to explain how to get set up and started in RStudio. We will also be using DataCamp for further R instruction through the semester.

Instructional Team:

Professor Adam J Sullivan, PhD adam_sullivan@brown.edu
TA Taylor Fortnam taylor_fortnam@brown.edu
TA Blain Morin blainmorin@brown.edu
TA Fuyu Zou fuyu_zou@brown.edu
Additional Tutoring / Office Hourse Julia Mullokandova julia_mullokandova@brown.edu

Class meetings:

What Where When
Lecture SPH - Room 375 Monday and Wednesday 10:30 - 11:50
Discussion/Lab SPH - Room 243 Monday 3- 4pm
Discussion/Lab SPH - Room 243 Wednesday 3- 4pm

Office Hours:

What Where When
Office Hours    
  SPH - Room 243 Wednesday 2:30 - 3:00 pm
  SPH - Room 241 Wednesday 4:00 - 5:00 pm
  SPH - Room 243 Friday 2:00 - 4:00 pm

Project Office Hours:

Please sign up for a slot for appointments. Sign up for 1 during this first week and then we can add more in the upcoming weeks.

Google Calendar Appointments

Additional Hours held by Julia Mullokandova: Click to View Julia's Hours

Additional Course Information via Main Menu

  • Syllabus and other course information and policies are available on the Course Syllabus

  • Lecture slides, reading assignments, homework, and other materials are available on the Calendar

  • Links to Online Course Textbooks and other references, software and other useful resources are provided on the Resource menu

  • Link to Links allows access to canvas, slack and the RStudio server.

  • Github for Class Github Organization

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