This webpage is only for the prospective students. You can enroll in this course officially and find more accurate details on Canvas.
Students will use R to manipulate data and perform exploratory data analysis using introductory statistics. A student completing this course can do these things:
Here is a more detailed course map.
Check the syllabus on Canvas.
An introductory statistics course. To be exact, no programming experience is necessary, but the basic stat, such as distributions, hypothesis testing, estimation, regression and simulation, is definitely needed!
The optional textbook is R in Action: Data Analysis and Graphics with R (2nd Ed) (with its liveBook) by Robert Kabacoff (2015) (good for Intermediate and Advanced R). Just use it for reference. Moreover, we’ll provide course notes, and we’ll read R documentation and write R code.
A laptop is required in class (better with a backup computer). If you have trouble with R, RStudio or R mark down in your own computer, try RStudio Cloud (without installation) or visit Computer lab locations - UW-Madison Information Technology.
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 me of their need for instructional accommodations by the end of the second week of the semester, or as soon as possible after a disability has been incurred or recognized. I, 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.
Any student signed up for honors should approach me within the first two weeks of the course to discuss a potential project. A timeline will be set up that helps students create their own project. Honors projects will be due at the end of the semester. If honors projects fail, a Q score will be assigned at the end of the session and the Dean Office can be contacted for further paperwork.
During the fall and spring, this course runs in five weeks. The weekly workload of this one-credit, five-week course should be like that of a three-credit, one-semester course: 1 credit = (3 credits/semester)*(1/3 semester).
These points are available (we might revise this as we write course materials):
| Total | 240 (Then, divided by 2.4 to convert to the points out of 100) |
|---|---|
| \(\approx\) 8 online quizzes (Quiz 1, …, Quiz 8) | \(\approx\) 93 |
| \(\approx\) 4 R or R Markdown scripts (hw1.R, hw2.R, hw3.Rmd, hw4.Rmd) | \(\approx\) 70 |
| Online exam on reading and writing R code | \(\approx\) 75 |
| Make a brief note in Piazza to introduce yourself before the end of the first week | \(\approx\) 1 |
| Answer a question on Piazza | \(\approx\) 1 |
We’ll assign grades according to the point scale, A = [92,100], AB = [88,92), B = [82,88), BC = [78,82), C = [70,78), D = [60,70), F = [0,60) (\(\ge\) 92% of points results in A); and according to the percentile scale, A = 70, AB = 60, B = 45, BC = 30, C = 10, D = 5, F = 0 (performing \(\ge\) 70% of the class leads to A). Your grade will be the higher of these two grades.
Grades are recorded in Canvas and you need to report any grading errors by the deadlines I will email you later.
If you anticipate religious or other conflicts with course requirements, you must notify me during the first two weeks of class. You may not make up missed quizzes, homework, or exams, 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).
Note that the registrar’s deadlines for our AEE session courses are special.
Check the Canvas Calendar.