Section 1

Class Schedule: Mondays 4:55 PM - 6.35 PM

Class Location: 31 Washington Pl, Room 414

Semester and Year: Fall 2023

Professor: Alex Dahlen, Ph.D.

Email: [email protected]

Stata   Lab   location:   238   Thompson   St

(GCASL) Room 388

Lab leader: Xinyu Wang

Email: [email protected]

R Lab location: 40 West 4th Street (Tisch)

Room LC11

Course Assistant: Phuc Vu

Email: [email protected]

STUDENT DROP-IN HOURS:

Feel free to come meet us to chat about the concepts in this course or anything else on your mind.  If these times and locations don’t work,send us an email and we’re happy to set up    some extra time, either in person or by zoom.

Alex Dahlen: Thursday 4-6pm, 708 Broadway, Room 415

Xinyu Want and Phuc Vu:  Wed. and Thurs. 3-4 pm, 708 Broadway, 3rd floor

COURSE DESCRIPTION:

This course covers basic probability, descriptive and inferential statistics, and the role of

biostatistics in the practice of public health. Specific attention will be given to common

probability distributions in public health and medicine, t-tests, Analysis of Variance, multiple  linear and logistic regression, categorical data analysis, and survival analysis. Statistical topics are presented conceptually with little derivation, and applications are demonstrated using common statistical software, Stata and R.

COURSE LEARNING OBJECTIVES AND RELATED COMPETENCIES AND COMPONENTS:

PRE-REQUISITES:

No pre-requisites

COURSE REQUIREMENTS AND EXPECTATIONS:

1. Lectures: Each lecture includes 1 – 4 modules consisting of brief (10-15 minutes) lectures   with accompanying PowerPoint presentations and associated material. Each week, a new lesson will go “live” in Brightspace. The content will stay up the entire semester. Students  should view lectures and review the accompanying lecture slides, as well as any additional information that is posted on the course website. Multiple viewings of lectures may be necessary to ensure full retention of the content.

2. Web Supplement: As a supplement to topics introduced in lectures, further information for

topics in each module and corresponding examples are provided on the web and should be read and understood by students each week. Web content is expected to take

approximately 60-90 minutes each week and are required learning. The course website in Brightspace also has additional web instructions/guidelines for using the Stata and R software. It is strongly encouraged that all students use this resource for additional help and reference.

3. Review Questions: At the end of each module, a set of review questions will allow students to identify areas for further attention/review. These must be completed prior to advancing to subsequent modules, but are ungraded. These will be brief, interactive quizzes where     questions are presented with answer choices. Students will select one of the possible

answer choices by clicking on their chosen button. Upon selection, student responses will be immediately noted as correct or incorrect and a brief explanation for each response

(whether correct or incorrect) will be provided. Students will have the opportunity to have further explanation with the help of a course assistant or the course instructor via

discussion sessions, email, or office hours.

4. Weekly Homework Assignments: Weekly homework assignments will be incorporated into each lecture and completed online. Assignments go live on Brightspace when the

corresponding weeks’ lesson is live. Be sure to check Brightspace for due dates.

Assignments are accessible in each Weekly Lesson or through the “Quizzes” tab in

Brightspace. Assignments will assess conceptual knowledge as well as the application of

principles using statistical programming. Please note that late homework is not accepted. All homework assignments must be submitted to the Brightspace site BY 5:00 PM on the due day (see course outline below) – late homework will not be accepted without the

instructor’s permission before it is due. Any unexcused homework not turned in by the due date will receive a grade of zero. Assignment due dates will also be found on Brightspace when posted.

It is strongly recommended that you take a screenshot of your submitted assignments for    safe keeping. There have been rare instances in the past where a student has submitted an  assignment that did not register in Brightspace. It will be far easier to receive credit for your assignment if you can submit proof that you submitted it before the deadline.

5. Readings will include a course textbook, additional resources, and reference materials. a. Course textbook:

Goodman, Biostatistics for Clinical and Public Health Research (2018). Routledge [Ebook available for review/download in NYU Libraries

https://ebookcentral-proquest-com.proxy.library.nyu.edu/lib/nyulibrary-ebooks/ detail.action?docID=5189163]

b.  Additional online readings showing the use of concepts in applied research will be posted

c.   You should complete the readings and/or view videos before each class session.

6. Software: You will be learning how to conduct these analyses using Stata and/or R. Students can choose Stata and/or R as their main statistical software package(s).

(1) Stata has been provided by the department and is available by using this link. You will need to complete a brief questionnaire in order to download the program. When

downloading R, first install the free R Software here. Next,download and install RStudio found here.

You can access this software free of charge at the following locations:

o Bobst Library 5th Floor Data Services Lab

o NYU virtual computer lab

Students can find real-time computer availability in the following website:

http://www.nyu.edu/life/information-technology/locations-and-facilities/student- technology-centers.html

Additionally, NYU data services has many helpful resources (https://guides.nyu.edu/stata, and https://guides.nyu.edu/r).

7. Exams: Two course sessions will be devoted to a midterm and final exam that will be

administered online and completed during a specified time period. The exams will be

multiple choice and follow the format and content knowledge of the CPH national exam.

NOTE: If you have questions about grades on any assignment or exam, speak to Dr. Spitzer within 3 days of receiving said grade.  After this timeframe, he will not entertain grading disputes.

GRADING COMPONENTS:

GRADING SCALE:

Note: Final grades are not rounded.

A:         94-100                         C+:        77-79

A-:      90-93               C:         73-76

B-:      80-82

D: 60-66

F: <60

BRIGHTSPACE:

Brightspace will be used extensively throughout the semester for assignments, announcements, and communication. Brightspace is accessible through at https://home.nyu.edu/academics

TECHNOLOGY POLICY:

You will need a PC or mac computer with access to Stata and R. A basic scientific calculator will also be required.

Mobile device (e.g., smart phones, pagers, etc.) ringers will be turned off or placed on vibrate

prior to class. Laptops and tablets can be used in the classroom to take notes, make calculations, and

download/read course materials. Research suggests that non-academic use of the internet is associated with poorer learning outcomes.

COURSE OUTLINE: