Description
Provides an understanding of the commonly used statistical language R. Students will learn to combine R with high performance computing tools to do scientific computing.

Learning Outcomes

Students will integrate R with high performance computing tools to do scientific computing at an introductory level. Here is a course map.

Requisites
STAT 304

Designations and Attributes
Breadth: Natural Science
Level: Intermediate
L&S Credit Type: Counts as Liberal Arts and Science credit (L&S)
Repeatable for Credit: No

Instructional Mode
Online

• See this schedule.
• There are seven topics in the schedule labeled "1. Optimization" through "7. Calling C++ from R via Rcpp". For each topic, there are links to two types of course materials:
  • There are lecture notes, each consisting of 1- to 3-page ".pdf" file.
  • There are screencast videos to guide you through the lecture notes and prepare you for the homework.
• There are three homework assignments, each requiring one or several hundred lines of code.
• There are three ways to get help:
  • Ask questions (or just listen in) at live Q&A web conferences at the "Class Times" listed below.
  • Ask a qustion via our asynchronous piazza Q&A site. Please feel free to answer other students' questions too.
  • Attend office hours (below) via web conference
• For each day in the schedule, do the things listed in its "Before Class" column before the web conference Q&A time that fits your schedule. Complete the things in the "Homework Due" column before 11:59 p.m.

Teachers

Name	Office Hours	Email (please ask most questions in person)
Instructor:
Gillett, John (Senior Lecturer)	?	jgillett@wisc.edu
Teaching Assistants:
?	?	?@wisc.edu
?	?	?@wisc.edu

Class Times
This online course meets during session DCC, 14 Jun - 04 Jul, 2021.
Live online help (optional) is available from the teacher and TAs via BBCollaborate web conference at these times:

week 1	Mo 6/14 John 10:25-11:25 am TA? 4:00-4:50 pm	Tu 6/15 John 10:25-11:25 am TA? 4:00-4:50 pm	We 6/16 John 10:25-11:25 am TA? 4:00-4:50 pm	Th 6/17 John 10:25-11:25 am TA? 4:00-4:50 pm	Fr 6/18 TA? 4:00-4:50 pm
week 2	Mo 6/21 John 10:25-11:25 am TA? 4:00-4:50 pm	Tu 6/22 John 10:25-11:25 am TA? 4:00-4:50 pm	We 6/23 TA? 4:00-4:50 pm	Th 6/24 John 10:25-11:25 am TA? 4:00-4:50	Fr 6/25 TA? 4:00-4:50 pm
week 3	Mo 6/28 John 10:25-11:25 am TA? 4:00-4:50 pm	Tu 6/29 TA? 4:00-4:50 pm	We 6/30 TA? 4:00-4:50 pm	Th 7/1: Exam

To attend a web conference, use your browser to visit https://canvas.wisc.edu/courses/?/external_tools/3041, click on "STAT305: ... - Course Room," and click "Join Course Room."

Textbook

No textbook is required. We'll provide course notes and online screencast lectures (and we'll read R documentation and write R code).

Optional Online Reading

R for Data Science by Garrett Grolemund and Hadley Wickham

An Introduction to R (pdf) by W. N. Venables, D. M. Smith and the R Development Core Team

Advanced R by Hadley Wickham (advanced)

Intro to R video lectures by Google Developers

R Programming wikibook

Using R for Data Analysis and Graphics by J. H. Maindonald

The R Inferno by Patrick Burns (advanced)

Optional Reference Books

R for Data Science by Garrett Grolemund and Hadley Wickham

Data Manipulation with R by Phil Spector

Advanced R by Hadley Wickham (advanced)

Introductory Statistics with R by Peter Dalgaard (2008)

R in a Nutshell by Joseph Adler (2009)

A Beginner's Guide to R by Alain F. Zuur, Elena N. Ieno, and Erik Meesters (2009)

Software for Data Analysis: Programming with R by John Chambers (2008) (advanced)

Computing
A computer is required that can run R, a statistical programming language, and RStudio, a free integrated development environment.

Help
The TAs and I are eager to help in class and office hours. Free drop-in tutoring is available in the Statistics Learning Center.

Credits and Grades
This is a 1-credit course.
45 Hours Per Credit -- One credit is the learning that takes place in at least 45 hours of learning activities, which include time in lectures or class meetings, in person or online, labs, exams, presentations, tutorials, reading, writing, studying, preparation for any of these activities, and any other learning activities.
During summer, this one-credit course runs in three weeks, which is 1/5 of a regular semester. The weekly workload of this course should be like that of a five-credit, one-semester course: 1 credit = (5 credits/semester)*(1/5 semester).

These points are available:

≈ 3 R scripts or projects	≈ 80
group practice exercises	≈ 20
Answer questions in Piazza	≈ 2
Total	102

We'll assign grades according to the percentage scale, A = [92,100], AB = [88,92), B = [82,88), BC = [78,82), C = [70,78), D = [60,70), F = [0,60) (92% of points => A); and according to the percentile scale, A = 70, AB = 50, B = 30, BC = 20, C = 10, D = 5, F = 0 (That is, performing better than 70% of the class => A. Here is a graph of this percentile curve.) Your grade will be the higher of these two grades.

Grades are recorded at https://canvas.wisc.edu/courses/?.

If you anticipate religious or other conflicts with course requirements, or if you require accommodation due to disability, you must notify me during the first three weeks of class. You may not make up missed course work except in the rare case of a documented, serious problem beyond your control.

I encourage you to discuss the course, including the online quizzes, with others, but you must write the R scripts and the exam by yourself and prevent others from copying your work. (See the UW Academic Integrity policy.)

Campus Spaces for Virtual Learning and Testing
Dedicated on-campus spaces with high-speed internet are available for students to reserve for any exam/quiz taken during the semester. Computers can also be requested.

Privacy of Student Information & Digital Tools: Teaching & Learning Analytics & Proctoring Statement
The privacy and security of faculty, staff and students' personal information is a top priority for UW-Madison. The university carefully reviews and vets all campus-supported digital tools used to support teaching and learning, to help support success through learning analytics, and to enable proctoring capabilities. UW-Madison takes necessary steps to ensure that the providers of such tools prioritize proper handling of sensitive data in alignment with FERPA, industry standards and best practices.
Under the Family Educational Rights and Privacy Act (FERPA which protects the privacy of student education records), student consent is not required for the university to share with school officials those student education records necessary for carrying out those university functions in which they have legitimate educationl interest. 34 CFR 99.31(a)(1)(i)(B). FERPA specifically allows universities to designate vendors such as digital tool providers as school officials, and accordingly to share with them personally identifiable information from student education records if they perform appropriate services for the university and are subject to all applicable requirements governing the use, disclosure and protection of student data.

Privacy of Student Records & the Use of Audio Recorded Lectures
See information about privacy of student records and the usage of audio-recorded lectures.
Lecture materials and recordings for this course are protected intellectual property at UW-Madison. Students in this course may use the materials and recordings for their personal use related to participation in this class. Students may also take notes solely for their personal use. If a lecture is not already recorded, you are not authorized to record my lectures without my permission unless you are considered by the university to be a qualified student with a disability requiring accommodation. [Regent Policy Document 4-1] Students may not copy or have lecture materials and recordings outside of class, including posting on internet sites or selling to commercial entities. Students are also prohibited from providing or selling their personal notes to anyone else or being paid for taking notes by any person or commercial firm without the instructor's express written permission. Unauthorized use of these copyrighted lecture materials and recordings constitutes copyright infringement and may be addressed under the university's policies, UWS Chapters 14 and 17, governing student academic and non-academic misconduct.

Students' Rules Rights, & Responsibilities
During the global COVID-10 pandemic, we must prioritize our collective health and safety to keep ourselves, our campus, and our community safe. As a university community, we must work together to prevent the spread of the virus and to promote the collective health and welfare of our campus and surrounding community.

UW-Madison Badger Pledge

UW-Madison Face Covering Guidelines
While on campus all employees and students are required to wear appropriate and properly fitting face coverings while present in any campus building unless working alone in a laboratory or office space.

Face Coverings During In-person Instruction Statement (COVID-19)
Individuals are expected to wear a face covering while inside any university building. Face coverings must be worn correctly (i.e., covering both your mouth and nose) in the building if you are attending class in person. If any student is unable to wear a face-covering, an accommodation may be provided due to disability, medical condition, or other legitimate reason.

Students with disabilities or medical conditions who are unable to wear a face covering should contact the McBurney Disability Resource Center or their Access Consultant if they are already affiliated. Students requesting an accommodation unrelated to disability or medical condition, should contact the Dean of Students Office.

Students who choose not to wear a face covering may not attend in-person classes, unless they are approved for an accommodation or exemption. All other students not wearing a face covering will be asked to put one on or leave the classroom. Students who refuse to wear face coverings appropriately or adhere to other stated requirements will be reported to the Office of Student Conduct and Community Standards and will not be allowed to return to the classroom until they agree to comply with the face covering policy. An instructor may cancel or suspend a course in-person meeting if a person is in the classroom without an approved face covering in position over their nose and mouth and refuses to immediately comply.

Quarantine or Isolation Due to COVID-19
Students should continually monitor themselves for COVID-19 symptoms and get tested for the virus if they have symptoms or have been in close contact with someone with COVID-19. Students should reach out to instructors as soon as possible if they become ill or need to isolate or quarantine, in order to make alternate plans for how to proceed with the course. Students are strongly encouraged to communicate with their instructor concerning their illness and the anticipated extent of their absence from the course (either in-person or remote). The instructor will work with the student to provide alternative ways to complete the course work.

Diversity & Inclusion
Diversity is a source of strength, creativity, and innovation for UW-Madison. We value the contributions of each person and respect the profound ways their identity, culture, background, experience, status, abilities, and opinion enrich the university community. We commit ourselves to the pursuit of excellence in teaching, research, outreach, and diversity as inextricably linked goals. The University of Wisconsin-Madison fulfills its public mission by creating a welcoming and inclusive community for people from every background -- people who as students, faculty, and staff serve Wisconsin and the world.

Academic Integrity
By virtue of enrollment, each student agrees to uphold the high academic standards of the University of Wisconsin-Madison; academic misconduct is behavior that negatively impacts the integrity of the institution. Cheating, fabrication, plagiarism, unauthorized collaboration, and helping others commit these previously listed acts are examples of misconduct which may result in disciplinary action. Examples of disciplinary action include, but is not limited to, failure on the assignment/course, written reprimand, disciplinary probation, suspension, or expulsion.

The members of the faculty of the Department of Statistics at UW-Madison uphold the highest ethical standards of teaching, data, and research. They expect their students to uphold the same standards of ethical conduct. Standards of ethical conduct in data analysis and data privacy are detailed on the ASA website, and include:

• Use methodology and data that are relevant and appropriate; without favoritism or prejudice; and in a manner intended to produce valid, interpretable, and reproducible results.
• Be candid about any known or suspected limitations, defects, or biases in the data that may affect the integrity or reliability of the analysis. Obviously, never modify or falsify data.
• Protect the privacy and confidentiality of research subjects and data concerning them, whether obtained from the subjects directly, other persons, or existing records.

Accommodations for Students with Disabilities
The University of Wisconsin-Madison supports the right of all enrolled students to a full and equal educational opportunity. The Americans with Disabilities Act (ADA), Wisconsin State Statute (36.12), and UW-Madison policy (Faculty Document 1071) require that students with disabilities be reasonably accommodated in instruction and campus life. Reasonable accommodations for students with disabilities is a shared faculty and student responsibility. Students are expected to inform faculty of their need for instructional accommodations by the end of the third week of the semester, or as soon as possible after a disability has been incurred or recognized. Faculty will work either directly with the student or in coordination with the McBurney Center to identify and provide reasonable instructional accommodations. Disability information, including instructional accommodations as part of a student's educational record, is confidential and protected under FERPA. (See: McBurney Disability Resource Center)

Academic Calendar & Religious Observances
See: https://secfac.wisc.edu/academic-calendar/#religious-observances

Complaints
If you have a complaint about a TA or course instructor, you should feel free to discuss the matter directly with the TA or instructor. If the complaint is about the TA and you do not feel comfortable discussing it with him or her, you should discuss it with the course instructor. Complaints about mistakes in grading should be resolved with the instructor in the great majority of cases. If the complaint is about the instructor (other than ordinary grading questions) and you do not feel comfortable discussing it with him or her, contact the Director of Undergraduate Studies, Professor Cecile Ane, cecile.ane@wisc.edu or the Director of Graduate Studies, Professor Bret Larget, bret.larget@wisc.edu. If your complaint concerns sexual harassment, please see campus resources listed at https://compliance.wisc.edu/titleix/resources/. In particular, there are a number of options to speak to someone confidentially. If you have concerns about climate or bias in this class, or if you wish to report an incident of bias or hate that has occurred in class, you may contact the Chair of the Statistics Department Climate & Diversity Committee, Professor Karl Rohe (karlrohe@stat.wisc.edu). You may also use the University's bias incident reporting system, which you can reach at https://doso.students.wisc.edu/services/bias-reporting-process/.