Summer 2020 - PSYC 210 D100

Introduction to Data Analysis in Psychology (4)

Class Number: 3157

Delivery Method: In Person

Overview

  • Course Times + Location:

    May 11 – Aug 10, 2020: Mon, 10:30 a.m.–12:20 p.m.
    Burnaby

  • Exam Times + Location:

    Aug 21, 2020
    Fri, 3:30–6:30 p.m.
    Location: TBA

  • 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).

Description

CALENDAR DESCRIPTION:

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

COURSE DETAILS:

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.

COURSE-LEVEL EDUCATIONAL GOALS:

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.
Quizzes:
There are twelve weekly quizzes on Canvas. The quizzes are designed to provide you with an opportunity to test your knowledge of the content for that week and motivate you to keep up with the course schedule. Each quiz will consist of approximately ten multiple choice questions. Students will have access to each quiz beginning Monday at 12:30pm and must complete it by the following Monday at 11:59pm. Only the marks from your top 10 quizzes will contribute towards your final grades. That is, your lowest two quiz scores will be dropped.
Exams:
There are two exams in this course: a midterm exam and a final exam. The final exam is cumulative, but most questions will come 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. The exams will include a combination of conceptual and computational questions. The exams will consist of timed quizzes in Canvas. The exams are open book (i.e., you can use any resources you wish in completing the exams). A calculator is required for both exams. See the midterm and final exam modules on Canvas for more details about the exams.

Grading

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

NOTES:

Remote Teaching:
Please note that all teaching at SFU in summer 2020 term will be conducted through remote methods. Enrollment in this course acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. No exams will be conducted in-person. Remote learning for this semester requires a computer or tablet, camera and internet access. For general assistance with remote learning see: https://www.sfu.ca/itservices/remote-study-work-resources.html
Canvas:
Canvas will be the main hub for this course. All course materials will be posted on Canvas (i.e., this syllabus, lecture slides, pre-recorded lectures, assignments, quizzes, exams, and other resources). Specifically, lecture slides and pre-recorded lectures will be available each week on Canvas. Important course announcements will also be posted on Canvas. Your main interaction with the team teaching will occur through Canvas. Additionally, you will be able to check your grades for all course components. You are also encouraged to use the discussion board and/or chat functions to contact other students about 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” or the following link (https://canvas.sfu.ca) 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. For technical assistance with Canvas see: http://www.sfu.ca/canvas/student-guide.html


Blackboard (BB) Collaborate:
This course will use Blackboard Collaborate in Canvas, specifically for all tutorials, office hours, and meetings. BB Collaborate is a real-time video conferencing tool that will be used primarily to host interactive tutorials. Tutorials will be held weekly at their originally scheduled days and times. Students are expected to attend their registered tutorial in real-time via BB Collaborate each week. Office hours as well as Q and A sessions will also be held on BB Collaborate each week. You can access BB Collaborate within Canvas from the course’s homepage.

Methods of Instruction:
Lectures will be pre-recorded and posted on Canvas on Mondays. Students are expected to watch the lectures prior to their tutorial each week. On Mondays, your instructor will also host a Q & A on BB Collaborate for students to ask questions about the course materials and components. Tutorials will be held in real time on BB Collaborate at their original times.

See the tables below for a breakdown of the course delivery.

Lecture


Section       Days & Times instructor Method
D100 Mondays Adam Blanchard pre-recorded on canvas
D101 Th 8:30 AM- 10:20 AM Keith Hamilton Live on BB Collaborate
D102 Th 10:30 AM- 12:20 PM Keith Hamilton Live on BB Collaborate
D103 Th 12:30 PM- 2:20 PM Regard Booy Live on BB Collaborate
D104 Th 2:30 PM- 4:20 PM Regard Booy Live on BB Collaborate
D105 Fri 10:30 AM - 12:20 PM Sungil Bang Live on BB Collaborate
D106 Fri 12:30 PM - 2:20 PM Sungil Bang Live on BB Collaborate
       
         

REQUIREMENTS:

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 come 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. The exams will include a combination of conceptual and computational questions. A calculator is required for both exams; graphing calculators and cellphones will not be permitted.

Materials

REQUIRED READING:

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

You can find a digital copy of the textbook at any of the following links:

https://us.sagepub.com/en-us/nam/essential-statistics-for-the-behavioral-sciences/book255139

https://www.vitalsource.com/en-ca/products/essential-statistics-for-the-behavioral-sciences-gregory-j-privitera-v9781506386287

https://www.amazon.com/s?k=9781506386300&ref=nb_sb_noss

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:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

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

TEACHING AT SFU IN SUMMER 2020

Please note that all teaching at SFU in summer term 2020 will be conducted through remote methods. Enrollment in this course acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes.

Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112) as soon as possible to ensure that they are eligible and that approved accommodations and services are implemented in a timely fashion.