There are two prerequisites for enrollment in EDUC/PSY 6600 (Research Design and Analysis I).
- Successful completion of EDUC/PSYCH 6570, which is a graduate level course in research methods. Alternative graduate-level research methods courses must have approval to be counted as a prerequisite for EDUC/PSY 6600.
- Passing a pretest. EDUC/PSY 6600 is a graduate-level statistics course that requires prior knowledge of basic statistical concepts. In EDUC/PSY 6600, students are required not only to read research findings and understand the analyses used, but also learn how to independently conduct statistical analyses of their data at a higher level. Students without exposure to or mastery of basic statistical concepts typically struggle with the content of EDUC/PSY 6600 and place an undue burden on the instructor, who must help them learn concepts they should have mastered previously. As an additional consequence, other students are disadvantaged because the time the instructor spends on remediation detracts from the time necessary to teach the objectives of EDUC/PSY 6600.
In 2005, the College of Education & Human Services began requiring students to pass a pretest covering the content of a typical undergraduate social science statistics course prior to registering for EDUC/PSY 6600. A student must obtain at least 70% correct on the pretest in order to enroll in EDUC/PSY 6600. The pretest consists of 30 randomly-selected multiple choice and true/false questions. Students have one hour to complete the pretest. Once you submit the quiz, you will be able to review your quiz responses while in the testing center only. Although notes, calculators, or other electronic devices are not permitted during the pretest, plain scratch paper and a pencil/pen are allowed. Students must pass the pretest within 5 business days of the first day of the semester in which they intend to enroll in the course. However, if the course is full by the time a student receives a passing score on the pretest, the student will not be able to register. Pretest scores are good for one year. Students who do not pass the pretest on the first attempt may take it up to two more times (total of 3 attempts). Students who do not pass the pretest on the third attempt will have to wait until the following semester to retake the pretest (with three more attempts available) and enroll in EDUC/PSY 6600 in a later semester. Pretest attempts and scores are reset approximately one week after the new semester begins. Although the pretest is not specific to any textbook, students who need additional preparation for the pretest may wish to review a textbook similar to Essentials of Statistics for the Behavioral Sciences by Gravetter and Wallnau. Resources for study and a practice pretest and with answers are found below.
The pretest is administered through the USU Testing Center, located on the main campus of Utah State University (south side of the Merril-Cazier Library). However, distance students may take the pretest at the nearest USU location in the state of Utah or at an out of state testing center through special arrangements. In order to take the pretest, students must first self-enroll to take the pretest via Canvas and then schedule a time to take the pretest at an USU Testing Center. Please check with the Testing Center well in advance to ensure that their facilities will be available for taking the pretest at the desired time and to also allow for multiple pretest attempts in case it is necessary to do so before the beginning of the semester. When you arrive at the USU Testing Center for your appointment, you will need to show your ID and they will assign you a computer and an access code to unlock the pretest.
In order to enroll in EDUC/PSY 6600 after receiving a passing score on the pretest, please email the Psychology Department Advisor with your A# and the desired section of the course (e.g., PSY or EDUC, semester, and which section if there are multiple sections). The advisor can also verify your completion of or enrollment in the other prerequisite, EDUC/PSY 6570, and lift the block so that you can register for EDUC/PSY 6600. If you have questions about this policy or if there are any problems in taking the pretest, please contact the 6600 Pre-Test Coordinator.
Refresher Resources for the EDUC/PSY 6600 Pretest
Below are several recommended resources to help you prepare to take the EDUC/PSY 6600 (Research Design & Analysis I) pretest. Each resource is free and includes several modules or resources that addresses aspects of the pretest. Please note that these resources are not created or maintained by Utah State University, nor are they specific to the EDUC/PSY 6600 course.Khan Academy: Statistics & Probability
The “Statistics and probability” modules provide good coverage of the topics included on the EDUC/PSY 6600 pretest. Each module is accompanied by videos and explanations. Topics that may be particularly useful include: displaying data, describing data, significance tests (one or more samples), confidence intervals, inference, ANOVA, and sampling distributions.Stanford University’s Probability and Statistics (Open + Free)
Stanford provides a self-paced online course on probability and statistics. As stated on their website: “The course is simply here for people who want to learn more about statistics.” Sections that may be of the most use include: “Exploratory Data Analysis” (especially histograms and other distribution discussions), “Producing Data” (the sampling material), and the “Inference” sections.Udacity: Intro to Statistics
Udacity offers a free statistics course aimed at beginners. The course covers many of the topics included on the EDUC/PSY 6600 pretest. You will need to set up a free account with them in order to watch the videos. Many of the videos are also available on YouTube. Some are very introductory and may be skipped if it is something you are already comfortable with.Carnegie Mellon University’s Open Learning Initiative: StatTutor Exercises
This site provides walk-through examples (no videos) that allow you to test your knowledge and learn as you go. You can also analyze real data using R or Excel.