Regression Analysis

EDUC 7610

Spring 2022

Instructor:
    Tyson S. Barrett, PhD
    tyson.barrett@usu.edu
    435-797-0120
    EDUC 456
Class:
    Tuesday and Thursday 4:30 pm - 5:45 pm
    HPER 114a and (when needed) Zoom Link (Posted on Canvas)
Office Hours:
    By appointment (via Zoom)

Materials:

Course Purpose:

Regression Analysis is designed to provide the student with a practical, applied approach to the application of fundamental behavioral and educational research design and statistical principles. Students will learn how to differentiate and appropriately select the best statistical methods for use in various research designs and analytical problems. This course will mostly focus on the general linear model, the building block of nearly all analyses discussed in EDUC/PSY 6600.

Two Prerequisites:

  1. Completion of EDUC/PSY 6570 (or approved equivalent)
  2. Completion of EDUC/PSY 6600

These prerequisites are mandated by the College of Education & Human Services to ensure that each student has the necessary background knowledge to be successful in this course. Both EDUC/PSY 6570 and EDUC/PSY 6600 must be completed with a passing grade prior to enrolling in EDUC/PSY 7610, precluding concurrent enrollment.

Course Structure:

This is a hybrid course; we will use both online recorded lectures and in-class activities. Students will be expected to demonstrate their learning via classroom participation, assignments, and examinations. The purpose of class activities is to elaborate on interesting or difficult material presented in the recorded lectures, conduct skill-building exercises and demonstrations, and to provide a forum for discussion. For this semester, all in-class activities will be done via Zoom.

Preparation & Attendance:

The nature of this course requires regular class attendance and participation. The student is therefore expected to watch the recorded lecture and read any assigned readings BEFORE each class session in order to be prepared for classroom activities and discussion (see ‘Discussions’ below). Students should not miss class activities as some material covered in class will not be covered anywhere else. All information covered in lectures and in-class activities can be used for examination questions.

Four Components of Your Grade:

I. Discussions, 25% of grade

By design, lectures are to enhance your understanding and experience with statistical concepts, rather than present them the first time (this is not an introductory course). It is of upmost importance that students read the material prior to the designated lecture, as well as read through the associated homework assignment. This ensures class time may be more valuably spent on answering higher level questions and preparing students for assignments, but more importantly for conducting your own research. To facilitate this, a lecture discussion point of the assigned lecture(s) is due on the day the material is covered in class before the lecture time begins. This discussion point is to be posted on canvas and should include a summary of ideas from the lecture, questions that you have regarding the material, or ways in which you can use the material in your research. Further, each student must respond to at least one other student’s point.

Each student must compose his or her own. Discussion points must NOT be a copy of the lecture notes. Discussion points will be posted before class on the due date (see course schedule) via CANVAS, but preferably much earlier so as to allow fellow students to comment on or answer your discussion point.

II. Assignments, 25% of grade

Three equally weighted unit assignments will form the basis for learning the practice of statistics at the level required by this course. The assignment is the application of unit material to the data you selected to use for your Final Project (discussed next). These assignments are flexible and provide you an opportunity to practice using the material for work that interests you and gives you a safe place to get things wrong (article reviewers are rarely all that kind…). Assignments require the manipulation and analysis of data, as well as professional communication of results. As such, these assignments are stepping stones leading to your full final project.

All assignments are required: no scores will be dropped. Assignments are due by 11:59pm on the due date (see course schedule).

IV. Final Project, 20% of grade

The Final Project will consist of using material from the class to write up a short article format. There is some flexibility to what the Final Project will look like and I recommend that you use it to help with theses, dissertations, or research articles. More information on this assignment will be discussed early on in the class. The project is due at the end of the semester.

IV. Examinations, 30% of grade

Four equally weighted examinations will be given during this course (see schedule). In order to avoid you needing to take the exam at the Testing Center, they will be given via Canvas using a tool known as Proctorio. Proctorio will record you taking your exam and will highlight any instances it believes you could be cheating. The benefit to using this approach is that you can take the exam any day during the week (Monday to Friday), whenever you feel is best. To use Proctorio, you will need to install the Proctorio Chrome Extension (only need to install once) and then take each exam in the Chrome browser. Examinations will generally require approximately 30-45 minutes. Examinations will cover material discussed in class and in the readings. All formulas needed will be provided on examinations (rarely will be needed, if at all). Calculators may be used (but unlikely to be needed), but not any electronic device that may transmit/receive, such as cell phones, iPods, tables, etc.

One of the four exams may be dropped (your lowest score, by default). Examinations will focus on the factual understanding of the methods and approaches discussed in class through multiple-choice questions and some short essay questions. Students may use the printed discussion points, homework, and other notes during examinations.

NOTE: No exam is comprehensive, however all prior material can be used on every exam.

Grading Criteria:

The standard grade breakdown used by Utah State University will be followed to assign the student a letter grade. The final percentage will be determined by dividing the student’s total points earned by the total number of possible points:

Grade Percentages
A > 93%
A- 90 - 92%
B+ 87 - 89%
B 83 - 86%
B- 80 - 82%
C+ 77 - 79%
C 73 - 76%
C- 70 - 72%
D 60 - 69%
F < 60%

Advice for Success:

Many of you will learn to appreciate, and may even develop a deep interest in, statistical analysis over the course of our semester together (hopefully!). You will likely see that statistical methods are tools in the social scientist’s toolkit, which will help you to better interpret and understand the applied research of your given field and will be of great value to you in conducting your own research.

However, I understand that many of you are concerned about any math required in the course. Although statistics is a branch of mathematics, in this applied course we keep the level of mathematics to a minimum – arithmetic and high school algebra. So, please do not let a fear of mathematics prevent you from excelling in this course. Some of you may also fear work on the computer. The practice of modern statistics relies almost exclusively on computer software. I believe that learning a statistical computing language or syntax is key to the learning of statistics. However, you should expect some frustration as you begin to use the statistical software in this course, but as you gain experience you will come to appreciate the power of statistical software as a tool for discovery. So, be patient with yourself and the material, and keep finding answers to your questions.

A final word of warning: Beware of technology misbehaving near deadlines. All summaries and assignments are to be turned in before the strict deadlines. Additionally, most assignments require some use of R or other software to complete them. It is unwise to count on technology to come through in time crunches.

R and RStudio:

In this course, we will use R and RStudio for the computation of all statistical techniques discussed in class. Both R and RStudio work together to make our statistical life easier. We use both for R is, metaphorically, the engine while RStudio is the pedals and steering wheel. That is, once R is installed, we will only need to open RStudio to do everything we’ll need to do. Both programs are free and, in general, can do much more with data and analyses than other programs. R can be downloaded from cran.cnr.berkeley.edu. RStudio can then be downloaded from https://www.rstudio.com/. Although the R syntax can be intimidating at first, we will cover all the syntax that you will need. My hope is that you will begin to feel comfortable using R to the point of using it in your own research.

Notably, there are many sources for learning more about R online, including several free books (e.g., tysonbarrett.com/Rstats). The reason this software was chosen for this class is because of its ability to reproducibly and succinctly run any analyses that you will be needing throughout your research and/or analytic career.

Note: An introductory R course is being offered concurrent to this course, Tuesdays at noon.

Selected Policies & Procedures:

Changes in Assignments and Schedule:

The instructor reserves the right to make changes to this syllabus at any time. Changes will be announced in class and posted on Canvas.

Children in class:

  1. All breastfeeding children are welcome as often as necessary.
  2. All non-nursing babies and children are welcome whenever alternate arrangements cannot be made. As a parent of three young children, I understand that babysitters fall through, partners have conflicting schedules, children get sick, and other issues arise.
  3. In cases where children come to class, I invite parents/caregivers to sit close to the door so as to more easily excuse yourself to attend to your child’s needs. As such, it is great if those seats are left available for any parents.
  4. All students are expected to join with me in creating a welcoming environment that is respectful of your classmates’ situations.

Inclusivity:

Professional courtesy and sensitivity are especially important with respect to individuals and topics dealing with differences of race, culture, religion, politics, sexual orientation, gender, gender variance, and nationalities. It is expected that all students will make all efforts to keep the classroom an inclusive environment.

Note: I will gladly honor your request to address you by an alternate name or gender pronoun. Please advise me early in the semester so that I may make appropriate changes to my records.

Students Needing Assistance with the English Language:

Several assignments in this course require English composition. If you feel you need assistance, please visit the USU Writing Center. They have tutors available to help: http://writingcenter.usu.edu.

Academic Integrity - “The Honor System”:

Each student has the right and duty to pursue his or her academic experience free of dishonesty. The Honor System is designed to establish the higher level of conduct expected and required of all Utah State University students.

The Honor Pledge: To enhance the learning environment at Utah State University and to develop student academic integrity, each student agrees to the following Honor Pledge: “I pledge, on my honor, to conduct myself with the foremost level of academic integrity .” A student who lives by the Honor Pledge is a student who does more than not cheat, falsify, or plagiarize. A student who lives by the Honor Pledge:

The vast majority of USU’s students follow these guidelines.

Plagiarism:

Plagiarism includes knowingly “representing, by paraphrase or direct quotation, the published or unpublished work of another person as one’s own in any academic exercise or activity without full and clear acknowledgment. It also includes the unacknowledged used ofmaterials prepared by another person or agency engaged in the selling of term papers or other academic materials.” The penalties for plagiarism are severe. They include warning or reprimand, grade adjustment, probation, suspension, expulsion, withholding of transcripts, denial or revocation of degrees, and referral to psychological counseling.

Sexual Harassment:

Sexual harassment is defined by the Affirmative Action/Equal Employment Opportunity Commission as any “unwelcome sexual advances, requests for sexual favors, and other verbal or physical conduct of a sexual nature.” If you feel you are a victim of sexual harassment, you may talk to or file a complaint with the Affirmative Action/Equal Employment Opportunity Office located in Old Main, Room 161, or call the AA/EEO Office at 797-1266

Students with Disabilities:

Reasonable accommodation will be provided for all persons with disabilities in order to ensure equal participation within the program. If a student has a disability that will likely require some accommodation by the instructor, the student must contact the instructor and document the disability through the Disability Resource Center (797-2444), preferably during the first week of the course. Any request for special consideration relating to attendance, pedagogy, taking of examinations, etc., must be discussed with and approved by the instructor.

Withdrawal Policy and “I” Grade Policy:

Students are required to complete all courses for which they are registered by the end of the semester. In some cases, a student may be unable to complete all of the coursework because of extenuating circumstances, but not due to poor performance or to retain financial aid. In such cases an ‘I’ will be submitted as the grade for the semester. The term ‘extenuating’ circumstances includes:

Tentative Schedule: