This page contains the syllabus for the course. This syllabus is an attempt early in the semester to plan for the course. This syllabus is subject to change at the Instructors discretion.

Course Information

PSQF 6250: Computer Packages for Statistical Analysis - Spring 2022

Instructor Information

  • Brandon LeBeau, Ph.D.
  • E-mail: brandon-lebeau at
  • Virtual Office Hours (Zoom): Thurs 1 pm to 2 pm or by appointment
    • See ICON for office hours zoom link
  • Department: Psychological and Quantitative Foundations, 361 LC
    • DEO: Dr. Foley Nicpon, 361 LC}

Course Quote

Data does not give up their secrets easily. They must be tortured to confess. – Jeff Hooper, Bell Labs

Course Description

This course aims to give students an in depth exploration of using R for data science and statistical analysis. The course is hands on where students will spend time practicing what they learn with real data to explore real problems. Students will gain experience cleaning, manipulating, visualizing, describing, exploring, and analyzing data from various perspectives. Students will also explore the benefits of reproducible analyses using R markdown documents to weave statistical code with text. Additional topics such as version control, markdown, and Monte Carlo simulation will be discussed. This course will not teach you exactly what to do for every analysis, rather will attempt to give you tools to accomplish general data tasks and practice answering questions with data.

Course Objectives

By the end of the course, students should be comfortable doing the following with R:

  • data visualization
  • data manipulation
  • data joining
  • descriptive analysis
  • fitting linear models
  • reproducible data analysis


No required textbook for purchase. There will be numerous online resources that will be used for the course. These are listed below and are posted on the ICON site. Note: You can click the links below and it will take you directly to the source on ICON.




Course Requirements

  • Online Quizzes (50 pts): Online quizzes through ICON will be given roughly every week. These will test basic knowledge of statistical programs covered in the course. Each quiz will be worth 5 points with 10 total quizzes. Quizzes will generally be due on Sunday evenings.
  • Assignments (50 pts): Homework assignments will be used to give hands on experience with the software. These homework assignments will give you an opportunity to answer questions with data, interpret results, and receive feedback on them. Each assignment will be worth 20 points with 5 total assignments. Students are able to work in groups of up to 3 for the course assignments. If students work in groups, all students will receive the same grade. Homework, including the R source code and written responses, will be submitted electronically on ICON.
  • Final Project Proposal (5 pts): This is a short, one page, proposal for the type of project you hope to complete. The goal of the final project proposal is to give you a chance to think about the final project earlier in the semester to get started on it. More details on what is intended in this proposal will be shared on the course website.
  • Final Project (25 pts): The final project gives you an opportunity to use data you are interested in to answer a question of interest. You will be expected to use descriptive statistics, fit a statistical model, and create at least one figure. More specific details will be shared on the course website.


  • Grading: Final grades will be based on the following weighting scheme:

    1. Quizzes: 50 points (5 points each – 10 quizzes)
    2. Assignments: 50 points (10 points each – 5 assignments)
    3. Final Project Proposal: 5 pts
    4. Final Project: 25 pts
  • Percentage Breakdown: Guidelines are given below, plus and minus grades will be given as well. If you wish to be graded on an S/U basis, please send me an email before the last day of classes (May 8, 2022).

  • A: 90% or better

  • B: 80% up to 90%

  • C: 70% up to 80%

  • D: 60% up to 70%

Course and University Policies

  • Absences: Absences happen. Therefore, I ask you to be as transparent as possible with me. I promise to be compassionate and understanding. If at any point in the semester you are having difficulties, please reach out to me and I will do my best to be accommodating and provide support, which could include an extension on course deadlines as necessary.
  • Announcements and Communication: Any announcements regarding the course will be communicated via e-mail so please check it daily. Course materials will be posted to ICON. Go to for access to the ICON site.
  • Adaptations and Modifications: Please inform me during the first two weeks if you require special adaptations or modifications to any assignment or due dates because of special circumstances such as learning disabilities, religious observances, or other appropriate needs.
  • Contesting a Grade: To contest a grade, please send me an e-mail detailing your reason within 48 hours of receiving the grade. This allows both of us time to think, reflect, and discuss the matter without taking class time from other students. When contesting a grade, provide a copy of the graded assignment.
  • Academic Misconduct: Plagiarism and cheating may result in grade reduction and/or serious penalties. Unless you are otherwise instructed, your work should be entirely your own. Please take care in writing your final project. You should always be writing in your own words, citing others' ideas, and quoting text as appropriate. This link provides the College of Education policy on student academic misconduct (plagiarism and cheating)
  • Free Speech and Expression: The University of Iowa supports and upholds the First Amendment protection of freedom of speech and the principles of academic and artistic freedom. We are committed to open inquiry, vigorous debate, and creative expression inside and outside of the classroom. Visit the Free Speech at Iowa website for more information on the university’s policies on free speech and academic freedom.
  • Accommodations for Students with Disabilities: The University is committed to providing an educational experience that is accessible to all students. If a student has a diagnosed disability or other disabling condition that may impact the student’s ability to complete the course requirements as stated in the syllabus, the student may seek accommodations through Student Disability Services (SDS). SDS is responsible for making Letters of Accommodation (LOA) available to the student. The student must provide a LOA to the instructor as early in the semester as possible, but requests not made at least two weeks prior to the scheduled activity for which an accommodation is sought may not be accommodated. The LOA will specify what reasonable course accommodations the student is eligible for and those the instructor should provide. Additional information can be found on the SDS website.
  • Absences for Religious Holy Days: The University is prepared to make reasonable accommodations for students whose religious holy days coincide with their classroom assignments, test schedules, and classroom attendance expectations. Students must notify their instructors in writing of any such Religious Holy Day conflicts or absences within the first few days of the semester or session, and no later than the third week of the semester. If the conflict or absence will occur within the first three weeks of the semester, the student should notify the instructor as soon as possible. See Operations Manual 8.2 Absences for Religious Holy Days for additional information.
  • Classroom Expectations: Students are expected to comply with University policies regarding appropriate classroom behavior as outlined in the Code of Student Life. While students have the right to express themselves and participate freely in class, it is expected that students will behave with the same level of courtesy and respect in the virtual class setting (whether asynchronous or synchronous) as they would in an in-person classroom. Failure to follow behavior expectations as outlined in the Code of Student Life may be addressed by the instructor and may also result in discipline under the Code of Student Life policies governing E.5 Disruptive Behavior or E.6 Failure to Comply with University Directive.
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  • Sexual Harassment/Sexual Misconduct and Supportive Measures: The University of Iowa prohibits all forms of sexual harassment, sexual misconduct, and related retaliation. The Policy on Sexual Harassment and Sexual Misconduct governs actions by students, faculty, staff and visitors. Incidents of sexual harassment or sexual misconduct can be reported to the Title IX and Gender Equity Office or to the Department of Public Safety. Students impacted by sexual harassment or sexual misconduct may be eligible for academic supportive measures and can learn more by contacting the Title IX and Gender Equity Office. Information about confidential resources can be found here. Watch the video for an explanation of these resources.
  • Mental Health: Students are encouraged to be mindful of their mental health and seek help as a preventive measure or if feeling overwhelmed and/or struggling to meet course expectations. Students are encouraged to talk to their instructor for assistance with specific class-related concerns. For additional support and counseling, students are encouraged to contact University Counseling Service (UCS). Information about UCS, including resources and how to schedule an appointment, can be found at Find out more about UI mental health services at:
  • Basic Needs and Support for Students: Student Care & Assistance provides assistance to University of Iowa students experiencing a variety of crisis and emergency situations, including but not limited to medical issues, family emergencies, unexpected challenges, and sourcing basic needs such as food and shelter. More information on the resources related to basic needs can be found at: Students are encouraged to contact Student Care & Assistance in the Office of the Dean of Students (Room 135 IMU, or 319-335-1162) for support and assistance with resources.