This electronic document is the official course syllabus. Any changes to this document will be announced in class and printed in red font. It was produced using R Markdown; the source .Rmd file is available on the course Canvas page under “Syllabus and Course Information”.

Course Information

OFFICIAL UNIVERSITY BULLETIN COURSE DESCRIPTION

This course introduces many important ideas in statistical computing. Students are expected to possess knowledge of mathematical statistics at the level of STAT 415 and matrices at the level of MATH 220. Students will learn the statistical computing environment called R and use R to implement many of the theoretical computing topics, which include numerical linear algebra, optimization, numerical and Monte Carlo integration, random number generation and simulation, and bootstrapping. Other statistical and mathematical software may be treated briefly, including symbolic mathematics environments like Mathematics and Maple.

Class Times and Locations:

Section Day/Time Location
002 MWF 12:20-1:10 Willard Bldg 365

Course Pre-requisites:

  • STAT 200 Elementary Statistics
  • MATH 220 Matrices
  • STAT 415 Introduction to Mathematical Statistics
  • Software experience with R (Recommended)

Teaching Team

Instructor

David Hunter
Office: 310 Thomas Building
Email: dhunter@stat.psu.edu

Teaching Assistant

Won Gu
Office: 301 Thomas
Email: wpg5129@psu.edu

Office Hours
Day When Where Who
Mondays 2pm - 3pm 310 Thomas Bldg Hunter
Thursdays 2pm - 3pm 310 Thomas Bldg Hunter
Tuesdays 2:30pm - 3:30pm 301 Thomas Gu

Also by appointment (to schedule: send an email with 3-4 possible times)

Course Materials:

  • Lectures will be based on a set of notes provided on Canvas
  • We will use Top Hat in class. Responses will not be graded, though a small amount of extra credit will be added for consistent participation over the course of the semester.
  • Optional book: Statistical Computing with R, 2nd edition by Maria L. Rizzo. This book is not required but shares a lot with lecture notes.

Computing

R will be used for the computing component of the course, and I strongly recommend that you download and install RStudio. R markdown is a tool for creating documents, written in plain text with lots of documentation, that I strongly recommended for submission of all homework assignments. Here are some free online resources available:

  • (FREE online) Introduction to R Markdown from RStudio
  • (FREE online): R for Data Science by Garrett Grolemund and Hadley Wickham
  • (FREE online): A Student’s Guide to R by Nicholas Horton, Randall Pruim, & Daniel Kaplan
  • (FREE online): Advanced R by Hadley Wickham
  • (FREE online): Quick-R by DataCamp

This syllabus was created using R markdown, and the .Rmd source file is available here.

Grading

  • 25% Homework (Drop Lowest 1 Grade)
  • 25% In-class quizzes (Drop Lowest 1 Grade)
  • 25% In-class midterm exam
  • 25% Final Exam
  • Up to 3% Extra Credit, including Top Hat participation

Late work

Homework and quizzes may not be turned in late. Midterm exam makeups are only permitted due to excused absences and with prior approval from the instructor.

Final Letter Grades

Grade Score
A > 93%
A- 90%
B+ 87%
B 83%
B- 80%
C+ 77%
C 70%
D 60%
F < 60%

Homework Assignments

Weekly homework assignments are due on Thursdays at 11:59:00 PM Eastern Time. You may work together in groups, but each student must submit their own written homework separately on Canvas.

Quizzes

There will be frequent in-class quizzes on many Fridays. Quizzes will be based on lectures and the homework problems. They will be closed book and without the aid of calculators or computers, though computing topics may be covered. There are no make-up opportunities for those who cannot attend class. The lowest quiz grade will be dropped.

Extra Credit

There may be occasional opportunities for extra credit, announced in class and on Canvas.

Policies & Resources

Counseling and Psychological Services (CAPS)

Many students at Penn State face personal challenges or have psychological needs that may interfere with interfere with their academic progress, social development, or emotional wellbeing. The university offers a variety of confidential services to help you through difficult times, including individual and group counseling, crisis intervention, consultations, online chats, and mental health screenings. These services are provided by staff who welcome all students and embrace a philosophy respectful of clients’ cultural and religious backgrounds, and sensitive to differences in race, ability, gender identity and sexual orientation.

Counseling and Psychological Services at University Park (CAPS):

Penn State Crisis Line (24 hours/7 days/week): 877-229-6400

Crisis Text Line (24 hours/7 days/week): Text LIONS to 741741

ECoS Code of Mutual Respect

The Eberly College of Science Code of Mutual Respect and Cooperation embodies the values that we hope our faculty, staff, and students possess and will endorse to make the Eberly College of Science a place where every individual feels respected and valued, as well as challenged and rewarded.

Academic Integrity

Unless the instructor tells you otherwise, you must complete all course work entirely on your own, using only sources that have been permitted by the instructor. If the instructor allows you to use ideas, images, or word phrases created by another person (e.g., from Course Hero or Chegg) or by generative technology, such as ChatGPT, you must identify their source. You may not submit false or fabricated information, use the same academic work for credit in multiple courses, or share instructional content. Students with questions about academic integrity should ask the instructor before submitting work.

All University and Eberly College of Science policies regarding academic integrity/academic dishonesty apply to this course and the students enrolled in this course. Refer to the following URL for further details on the academic integrity policies of the Eberly College of Science: http://www.science.psu.edu/academic/Integrity/index.html.

Disability Statement

Penn State welcomes students with disabilities into the University’s educational programs. If you have a disability-related need for reasonable academic adjustments in this course, contact Student Disability Resources (SDR; formerly ODS) at 814-863-1807, 116 Boucke, http://equity.psu.edu/student-disability-resources. In order to receive consideration for course accommodations, you must contact ODS and provide documentation (see the guidelines at http://equity.psu.edu/student-disability-resources/guidelines).

Educational Equity/Report Bias Statement

Penn State takes great pride to foster a diverse and inclusive environment for students, faculty, and staff. Acts of intolerance, discrimination, or harassment due to age, ancestry, color, disability, gender, gender identity, national origin, race, religious belief, sexual orientation, or veteran status are not tolerated and can be reported through Educational Equity via the Report Bias webpage.

Campus Emergencies

Campus emergencies, including weather delays, are announced on Penn State Live and communicated to cellphones, email, and the Penn State Facebook page.