Summer 2021 - PSYC 210 D100

Introduction to Data Analysis in Psychology (4)

Class Number: 3828

Delivery Method: In Person

Overview

  • Course Times + Location:

    Mo 12:30 PM – 2:20 PM
    REMOTE LEARNING, Burnaby

  • Exam Times + Location:

    Aug 13, 2021
    12:00 PM – 3:00 PM
    REMOTE LEARNING, Burnaby

  • 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:

Note that PSYC 210 will be using a combined learning strategy. Lectures will be asynchronous, but office hours, exams, and tutorials will be synchronous.

This course introduces students to statistical concepts and techniques applied in the field of psychology. Successful completion of the course is a requirement for students to formally declare as a psychology majors within the department. The course aims to teach students three broad categories of statistical knowledge. First, students will learn how to organize, describe, and represent actual data (e.g., measures of central tendency and dispersion, tabular and graphical displays of data, etc.), as well as be introduced to fundamental concepts such as measurement, sampling, and probability. Second, students will learn the conceptual frameworks for assessing the probability of sample data (e.g., standardized scores, sampling distributions, and null hypothesis significance testing). Finally, students will learn to apply those frameworks by conducting inferential statistical tests applicable to numerous research scenarios (e.g, single- and multiple-group designs, between- and within-subjects designs).

COURSE-LEVEL EDUCATIONAL GOALS:

Upon successful completion of this course, it is my aim that students are able to:

• Employ basic descriptive statistics, graphs, and tables to summarize sample data

• Explain the role of sampling distributions and z-scores in the logic of inferential statistics

• Apply the logic of null hypothesis significance testing by translating psychological research questions into testable research hypotheses and articulating the appropriate null and alternative hypotheses

• Choose appropriate statistical analyses for the testing of psychological hypotheses

• Interpret the meaning of a p-value with respect to reject or non-rejection of a null hypothesis and interpret p-values in published psychological research

• Conduct and interpret hypothesis tests on behavioral data using z-tests and t-test

• (If time permits) Understand the core concepts of analysis of variance (ANOVA) and why it is favoured over multiple t-tests • Understand the core concepts of simple ordinary least squares regression, including calculating the slope parameter, intercept parameter, and predicted scores, as well as conduct tests of model fit

Grading

  • Assignment 1: 20%
  • Assignment 2: 20%
  • Midterm Exam: 30%
  • Final Exam: 30%

NOTES:

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

Letures: 
nstruction for this course will utilize a combined learning strategy. Lectures will be asynchronous, but office hours, exams, and tutorials will be synchronous.

The details provided here for the grading evaluation and number of assignments are subject to change or alteration before the beginning of the course. Please refer to the published course syllabus for the finalized details of the course. All other details of the course presented here are finalized.

Materials

RECOMMENDED READING:

David C. Howell, Statistical Methods for Psychology.  8th edition.  Cenage.
ISBN: 9781133713272

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 2021

Teaching at SFU in summer 2021 will be conducted primarily through remote methods, but we will continue to have in-person experiential activities for a selection of courses.  Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment 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. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.

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).