Instructor: Isaac Quintanilla Salinas
Email: iquin002 [AT] ucr [DOT] edu
Office Hours: MW 9 AM - 11 AM
TA: Dylan Friel
Email: dfriel001 [AT] ucr [DOT] edu
Office Hours: Tuesday: 10 AM - 12 PM PDT
All office hours and meetings will occur on zoom. Please visit canvas for zoom information.
Lecture
Meeting Times: MW 8-11 AM (Asynchronously)
Discussion
Meeting Times: MW 11 AM - 12 PM
Introduction to Statistical Computing: 4 Units; Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 100A or equivalent. Introduction to computer-assisted data analysis and statistical inference using both the R and SAS packages. Topics include input, output, and editing of data; graphical procedures; descriptive statistics; cross-tabulation; inferential statistical techniques including estimation and testing; and analysis of variance.
For this course, we will use R and RStudio. Please download and install on your computer.
R is a free statistical software program that is available for download at: https://www.r-project.org/.
RStudio provides free and open source tools for your data analysis in R: https://www.rstudio.com/
R Cookbook, 2nd edition (2019), J.D. Long and Paul Teetor, ISBN: 978-1492040682. An electronic copy of the textbook is freely available at https://rc2e.com/.
R Graphics Cookbook: Practical Recipes for Visualizing Data, 2nd edition (2020), Winston Chang, ISBN: 978-1491978603. An electronic copy of the textbook is freely available at https://r-graphics.org/.
R Markdown: The Definitive Guide, 1st edition (2020), Yihui Xie, J.J. Allaire, and Garrett Grolemund, Published by Chapman & Hall/CRC, ISBN: 978-1138359338. An electronic copy of the textbook is freely available at https://bookdown.org/yihui/rmarkdown/.
R for Data Science, 1st edition (2017), Hadley Wickham and Garrett Grolemund, ISBN: 978-1491910399. An electronic copy of the textbook is freely available at https://r4ds.had.co.nz/
Zoom: ucr.zoom.us
Canvas: elearn.ucr.edu
RStudio Cloud: rstudio.cloud
Course Website: s147.inqs.info
At the conclusion of this course, students will be able to:
Comfortably navigate RStudio and understand R programming fundamentals, including syntax and coding best-practices
Import, access, manipulate, and summarize data sets in R
Create and edit visualizations in R
Understand and use R functions, including creating custom functions and installing new function packages into the R workspace
Perform basic statistical analysis using R such as producing descriptive statistics, plots, and regression models
Use R Markdown to integrate R code into reports/documents for reproducibility
| Category | Percentage |
|---|---|
| Participation | 10% |
| Labs | 20% |
| Homework | 25% |
| Tutorial Book | 15% |
| Final (cumulative) | 30% |
At the end of the quarter, course grades will be assigned according to the following scale:
| A+ | 98 – 100 | B+ | 87 – <90 | C+ | 77 – <80 | D+ | 67 – <70 | ||
| A | 93 – <98 | B | 83 – <87 | C | 73 – <77 | D | 63 – <67 | F | < 60 |
| A– | 90 - <93 | B- | 80 – <83 | C– | 70 – <73 | D– | 60 – <63 |
Lectures will be held asynchronously using video recordings. Students are encouraged to take notes while watching the videos.
Student participation will be measured by weekly check-ins with the instructor. Check-in with the instruction for 5-10 minutes during the instructor’s office hours. If you are not able to attend office hours, please contact the instructor to meet at another time.
Discussion is led by the TA and will be held using Zoom during the scheduled discussion time. The TA will be available to assist students with their weekly lab assignments which are designed to prepare you for the homework that is due during the week. Students will need to complete the labs in order to complete the HW assignment. Students can also ask questions regarding course material and homework assignments. Attendance will not be taken. Students will be allowed three submission attempts, with only the last submission being graded.
Homework assignments will consist of study problems in preparation for the final exam. HW will be assigned and due weekly. Students may discuss homework assignments with classmates but should complete the work on their own. Students will be allowed two submission attempts, with only the last submission being graded. Due to the nature of the course, I encourage everyone to begin the assignment as soon as possible.
The Tutorial Book will be a collection of tutorials students create via RMarkdown. The idea is to create a “book” explaining how to conduct different topics. Each “chapter” will be a tutorial on an assigned topic. At the end of the quarter, students will submit the collection of RMarkdown files for a final grade.
The final exam will be cummulative take-home exam. You will have 24 hours to complete the exam and turn it in by the deadline.
There will be 2 extra credit opportunities throughout the summer. Each opportunity can raise your overall grade by 4 percentage points. The extra credit opportunities are listed below:
RMD Diagnostics (Due: Sunday (7/11/21) @ 11:59 PM PST)
Create a website with RMarkdown (Due: Sunday (7/18/21) @ 11:59 PM PST)
Discussion Boards in Canvas are the preferred method of communication regarding course material. Posts can be used for asking general questions that your classmates might also be interested in or can contribute to. Topics can range from questions about a particular topic covered in the course to homework questions to technology questions. The Instructor and/or TA will regularly check the discussion boards and contribute appropriately. Proper conduct and etiquette are expected.
Email is the preferred method of communication regarding personal concerns. Please use professional etiquette when sending an email to the Instructor and/or TA. In addition, the email should include the course name (i.e., STAT 147) in the subject line of the email and your name & SID in the body of the email. Emails will be responded to within 24 hours and usually much sooner, including emails sent over the weekend.
Late assignments will be accepted 24 hours after the assigned due date with a penalty. Assignments submitted within 24 hours after the deadline will only receive a 50% deduction of the overall grade. Any assignments (assignments include video notes, practice exercises, labs, homework, or any other assigned work with a due date) submitted after the 24 hour grace period will not be accepted. The final exam will receive a 25% deduction for each additional hour it is late. Important: Last minute computer failures, illnesses, etc. will not excuse missed deadlines. Please plan accordingly.
In general, there are no make-ups allowed. However, under extenuating circumstances, the instructor may decide at his discretion to authorize make-up work to be completed. The student is required to contact the instructor via email as soon as they become aware that a make-up is needed, but no later than 24 hours in advance (or 24 hours after the missed work when the absence is due to an emergency). Proper documentation must be provided to support the student’s need for a make-up (i.e., doctor’s note, legal document, etc.)
| Week | Time | Topic |
|---|---|---|
| 1 | Mon | Introduction to R, RStudio, Data Types, Data Frames, Vectors, R Functions, and Scripting |
| 1 | Wed | Introduction to R Packages, RMarkdown, Descriptive Statistics Functions |
| 2 | Mon | Campus Holiday: Juneteenth |
| 2 | Wed | Matrices, Lists, Subsets, and Indexing, Directories, Workspaces, R Projects, Reading & Writing Data, Manipulating Data, Creating Data Frames, and Variables |
| 3 | Mon | Campus Holiday: Independence Day |
| 3 | Wed | Control Flow (Loops and Conditional Statements) |
| 4 | Mon | Plotting with Base R & ggplot2 |
| 4 | Wed | Hypothesis Testing and Regression Models |
| 5 | Mon | Writing Functions |
| 5 | Wed | Intro to dplyr |
| Final | TBD |
| Week | Due Date | Assignments |
|---|---|---|
| 1 | Tue (6/22/21) | Lab 1A Due @ 11:59 PM PST |
| 1 | Thu (6/24/21) | Lab 1B Due @ 11:59 PM PST |
| 1 | Sat (6/26/21) | HW 1 Due @ 11:59 PM PST |
| 2 | Tue (6/29/21) | Lab 2A Due @ 11:59 PM PST (Cancelled) |
| 2 | Thu (7/01/21) | Lab 2B Due @ 11:59 PM PST |
| 2 | Sat (7/03/21) | HW 2 Due @ 11:59 PM PST |
| 3 | Tue (7/08/21) | Lab 3A Due @ 11:59 PM PST |
| 3 | Thu (7/09/21) | Lab 3B Due @ 11:59 PM PST |
| 3 | Sat (7/10/21) | HW 3 Due @ 11:59 PM PST |
| 3 | Sun (7/11/21) | EC 1 Due @ 11:59 PM PST |
| 4 | Tue (7/13/21) | Lab 4A Due @ 11:59 PM PST |
| 4 | Thu (7/15/21) | Lab 4B Due @ 11:59 PM PST |
| 4 | Sat (7/17/21) | HW 4 Due @ 11:59 PM PST |
| 4 | Sun (7/18/21) | EC 2 Due @ 11:59 PM PST |
| 5 | Wed (7/21/21) | Tutorial Book Due @ 11:59 PM PST |
Highly Recommended: Laptop (Mac or PC)
Chromebooks, Tablets, or Pi´s use rstudio.cloud
You will need a reliable internet connection. Test your internet speed using speedtest.net. Recommended internet speeds:
If you do not have or cannot acquire these items, you can apply to the Loan2Learn program to get a loaner device. Please keep me aware of any difficulty or delay in acquiring these devices.
If you choose to withdraw from this course, you must complete the appropriate University form and turn the form in before the deadline. Deadlines are shown in the Academic Calendar, which is available from the Office of the Registrar.
UCR is committed to upholding and promoting the values of Integrity, Accountability, Excellence, and Respect. As a student in this class, it is your responsibility to act in accordance with these values by completing all assignments in the manner described, and by informing the instructor of suspected acts of academic misconduct by your peers. Should you choose to commit academic misconduct in this class, you will be held accountable according to the policies set forth by the University, and will incur appropriate consequences both in this class and from Student Conduct and Academic Integrity Programs. It is the responsibility of each student to be familiar with the definitions, policies, and procedures concerning academic misconduct. Please revisit Academic Integrity Policies and Procedures for more information. This site also defines misconduct, provides examples of prohibited conduct, and explains the sanctions available for those found guilty of misconduct. It is expected that you will ask for clarification if you have questions or concerns regarding any of the expectations of this class.
UC Riverside is committed to providing equal access to learning opportunities to students with documented disabilities. To ensure access to this class, and your program, please contact the Student Disability Resource Center (SDRC) to engage in a confidential conversation about the process for requesting accommodations. More information can be found at the Student Disability Resource Center. If you are a student registered with the SDRC, please ensure you request your quarterly accommodations through R’Ability.
Student Health Services, Counseling & Psychological Services (CAPS), Residential Life, Dining, and R’Pantry are available to support students.
It is the policy of the University to excuse absences of students that result from religious observances and to provide for the rescheduling of examinations and additional required classwork that may fall on religious holidays without penalty. It is the responsibility of the student to make alternate arrangements with the instructor at least one week prior to the actual date of the religious holiday.
For any concerns regarding gender-based discrimination, sexual harassment, sexual misconduct, stalking, or intimate partner violence, the University offers a variety of resources, including advocates on-call 24/7, counseling services, mutual no contact orders, scheduling adjustments, and disciplinary sanctions against the perpetrator. Please see the Title IX website for more information. They can be reached at (951) 827-7070. You can also file a report.