STAT 4194 @ OSU
Spring 2019 Dalpiaz
STAT 4194 | OSU | Dalpiaz
Syllabus RStudio Carmen
Readings References R Practice Projects
Week 1
- Tuesday | 2019.1.8
- First day of class! Syllabus discussion and course overview. Maybe some
Rdiscussion.
- First day of class! Syllabus discussion and course overview. Maybe some
- Thursday | 2019.1.10
- Presentation by the OSU Advancement Office, this semester’s data partner.
Week 2
- Tuesday | 2019.1.15
- How much R do we remember? Some brief remarks on data ethics.
- Thursday | 2019.1.17
- Begin discussion of practice project.
- Friday | 2019.1.18
- Deadline: Reading Quiz
Week 3
- Tuesday | 2019.1.22
- Work on practice projects
- Thursday | 2019.1.24
- Project presentations
- Deadline: Project Presentation
- Friday | 2019.1.25
- Deadline: Project Summary
- Deadline: Project RMarkdown
Week 4
- Tuesday | 2019.1.29
- Discussion of practice projects
- Thursday | 2019.1.31
- Introduce first midterm project
Week 5
- Tuesday | 2019.2.5
- Group meetings with data provider and project work time.
- Thursday | 2019.2.7
- Group meetings with Dave and project work time.
Week 6
- Tuesday | 2019.2.12
caretoverview. Project work time.
- Thursday | 2019.2.14
- Project work time.
Week 7
- Tuesday | 2019.2.19
- Project work time. Indroduction to second midterm project.
- Deadline: Midterm Project I
- Thursday | 2019.2.21
- Project work time.
Week 8
- Tuesday | 2019.2.26
- Group meetings with data provider and project work time.
- Thursday | 2019.2.26
- Project work time.
Week 9
- Tuesday | 2019.3.5
- Project work time.
- Thursday | 2019.3.7
- Project work time.
- Deadline: Midterm Project II Presentations (Documention due previous day.)
- Deadline: Midterm Project II RMarkdown (Due on Friday.)
Week 10
- Tuesday | 2019.3.12
- No class. Spring Break!
- Thursday | 2019.3.14
- No class. Spring Break!
Readings
The following list are suggested readings, some of which will be assigned throughout the semester. This list will grow during the semester.
- Kass et al. - Ten Simple Rules for Effective Statistical Practice
- Breiman - Statistical Modeling: The Two Cultures
- Donoho - 50 Years of Data Science
- Box - Science and Statistics
- Wickham - Tidy Data
- Delgado et al. - Do we Need Hundreds of Classifiers to Solve Real World Classification Problems?
- Benjamin et al. - Redefine Statistical Significance
- Winston - How to Speak
- Domingos - A Few Useful Things to Know about Machine Learning
References
The following is an incomplete list of useful references which will be updates throughout the semester.
- Wickham and Grolemund - R for Data Science
- Dalpiaz - Applied Statistics with R
- Dalpiaz - R for Statistical Learning
- Wickham - Advanced R
- Burns - The R Inferno
- Gillespie and Lovelace - Efficient R Programming
- Xie, Allaire, and Grolemund - R Markdown: The Definitive Guide
- RStudio - RStudio Cheat Sheets
- Bryan, Hester - Happy Git and GitHub for the useR
- Bryan, Hester - WTF: What They Forgot to Teach You About R
- Misc. - R Weekly