Spring 2020 - PSYC 210 D900

Introduction to Data Analysis in Psychology (4)

Class Number: 7626

Delivery Method: In Person


  • Course Times + Location:

    Mo 10:30 AM – 12:20 PM
    SRYC 5080, Surrey

  • Exam Times + Location:

    Apr 24, 2020
    8:30 AM – 11:30 AM
    SRYC 3310, Surrey

  • Prerequisites:

    PSYC 201W and BC high school Math 12 with a minimum grade of C (2.0) or BC high school Math 11 with a minimum grade of B- (2.67) or any level MATH or STAT course with a C- (1.67) or FAN X99 taken at SFU with a minimum grade of C (2.00).



Covers basic descriptive and inferential techniques most appropriately applied to the various forms of data from psychological research. Quantitative.


This course provides an introduction to fundamental descriptive and inferential statistics commonly used in contemporary psychological research. Statistical methods play a crucial role in the translation of empirical data into reasonable descriptions and conclusions. This course introduces a variety of statistical techniques for displaying and describing research data, as well as a range of statistical methods for drawing sound conclusions from research data. Specific topics that will be covered include displaying data, measures of central tendency and variability, probability, standard scores, sampling distributions, the logic of hypothesis testing, hypothesis tests on means (i.e., Z-tests, one-sample t-tests, related samples t-tests, independent samples t-tests, and ANOVA), and basic methods for correlation and regression. The main goals of the course are to introduce students to the role of statistics in the description and analysis of data from commonly used research designs and to the underlying logic inherent to inferential statistical analysis. Hand calculators are required. Knowledge of basic mathematical functions and basic algebra are assumed. No special software will be used. Although some calculation will be required, the emphasis is placed on providing a solid theoretical understanding of introductory statistical methods.


Assignments: There are three written assignments required in this course. The assignments are designed to provide you with an opportunity to practice thinking and writing about statistical concepts, as well as practice computing the core statistical techniques reviewed in the course. Each of the assignments will consist of a combination of conceptual and computational questions.

Exams: There are two exams in this course: a midterm exam and a final exam. The final exam is cumulative, but most questions will comes from the second half of the course. All material covered in the lectures and assigned textbook readings is testable. Exams will consist of multiple choice and short answer questions


  • Assignment #1: 10%
  • Assignment #2: 10%
  • Assignment #3: 10%
  • Midterm Exam: 30%
  • Final Exam: 40%


Special Arrangements and Grades:     
Note that failure to complete any of the evaluative components for this course will result in a score of zero for that component and a final letter grade of N (incomplete). That is, all assignments and exams must be completed in order to receive a final letter grade for the course. Special arrangements for the taking of an exam must be made in the first two weeks of the semester. Note that it is not guaranteed that you will be granted an alternate sitting for an exam. Make-up exams will be given only in the event of a valid and documented emergency (e.g., documented illness, death of a family member) or university approved conflict (e.g., approved athletic event, religious holiday). There must be a clear association between the reason provided and the inability to attend the exam as scheduled. If you must miss an examination for an emergency or other reason, you should contact the instructor prior to the scheduled exam time or as soon as possible in order to schedule a time to complete the missed exam. You must provide written documentation of the emergency or other reason in order to schedule a make-up exam. If you miss an exam due to a medical illness, you must get your doctor to sign and complete the Certificate of Illness Form available from Student Services (https://www.sfu.ca/content/dam/sfu/students/pdf/certificate-of-illness.pdf). 

Attendance: It is strongly recommended that you attend all lectures and tutorials. If you are unable to attend a lecture or tutorial, please reach out to a fellow classmate to get any notes and materials or information that go beyond the lecture slides. Of note, the lecture slides are not a substitute for a missed lecture. The lecture slides contain a great deal of material that will be covered in lecture, but they do not contain all the information necessary for you to know in this course. That is, all information conveyed in lecture is eligible for inclusion on the exams, and the exams will cover material presented in lecture that may go beyond what is included in the textbook or lecture slides.

Preparation: It is strongly recommended that you read the relevant readings before you attend lecture each week. Completing the relevant readings prior to lecture will allow you to more fully participate in class activities, ask more focused questions, and gain a more nuanced understanding of the material. Students that keep up with the required readings and course activities will generally perform better on the evaluative components of the course than other students.

Participation: Class participation is an important component of this course. It is strongly recommended that you come prepared to actively participate in lecture and tutorials. Activities in tutorials will involve interactive learning, discussion, and demonstrations. Please be prepared to get involved, discuss, learn from each other, and have fun. Your participation and engagement in lectures and tutorials is highly encouraged and valued.

Electronics: Electronic recording of lectures and tutorials is explicitly prohibited without the consent of the instructor and/or teaching assistant. When recordings are permitted, they are solely for the use of the authorized student and may not be reproduced or shared with others without the explicit consent of the instructor.  Laptops and tablets can be extremely useful for note-taking and other class activities. As such, you are welcome and encouraged to bring these to class. However, these devices can be distracting to fellow students around you. As such, please keep your screen on topic. Students using their devices for activities unrelated to the course should sit at the back of the room.   Cellphones should be turned to silent during lecture and tutorials. If you need to use your cellphone during lecture or tutorial, please be respectful of the rest of the class and step out of the classroom. 


Canvas: This course will use Canvas. Most course materials will be posted on Canvas (i.e., this syllabus, lecture slides, assignments, and other resources). Important course announcements will also be posted on Canvas. Additionally, you will be able to check your grades for all course components. You are also encouraged to use the discussion board or chat functions to contact other students about missed lectures, post questions or clarifications about the course concepts, or organize study sessions with your classmates. You can access Canvas from the SFU homepage, click on “sign in” then on “Canvas” and sign in with your SFU login information. Once signed in, you will see a list of the courses you are taking that are using Canvas each semester.



Privitera, G. J. (2019). Essential statistics for the behavioral sciences (2nd ed.). Los Angeles, CA: Sage.

The textbook comes with an online platform called SAGE edge. This resource provides a variety of material for each chapter, including videos, graphics, summaries, and quizzes designed to assist you in understanding the material and help you prepare for exams. Making use of this online resource is optional, but many students find it is a great assistance in understanding the course material.

Registrar Notes:

SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html