August 2022 Introduction to Psychological Statistics McGill University, Department of Psychology Course Syllabus ** Schedules, offices, office hours, due dates, and assigned readings can change, visit the myCourses site for the most up to date version of this syllabus and a change log ** What: PSYC 204: Introduction to Psychological Statistics Prerequisite / Co-requisite: High School Algebra Where: MCMED 522 When: Tuesdays and Thursdays 10:05a to 11:25a Who (Instructor): Dr. Jessica Kay Flake Office: 2001 McGill College, 754 Email: Jessica.flake@mcgill.ca Office Hours: From 11:25a to 12:00p on Tuesday and Thursdays (right after class, can answer questions in the hall and/or walk down to office to meet students) Faculty page: https://www.mcgill.ca/psychology/jessica-kay-flake Twitter: @JkayFlake *check out my twitter for all stuff quant methods relevant to the social sciences Who (Teaching Assistants): Teaching Assistant Assigned Students Email Zoom link (if online) | Office Hour | Tutorial Time Sean Devine A-C sean.devine@mail.mcgill.ca https://mcgill.zoom.us/my/sdevine Mondays 11:00AM | Mondays 10:00AM Michael Ilagan D-J michael.ilagan@mail.mcgill.ca Location TBD Tuesdays 2:00 pm | Tuesdays 1:00 pm Bellete Lu K-M yingke.lu@mail.mcgill.ca Room 464 Thursdays 3:30 pm | Thursdays 2:30 pm Jake Plantz Jennifer Suliteanu N-S T-Z Jacob.plantz@mail.mcgill.ca jennifer.suliteanu@mail.mcgill.ca https://mcgill.zoom.us/j/9568349932 Thursdays 1:05 pm | Thursdays 12:05 pm Location TBD Wednesdays 2:00 pm | Wednesdays 1:00 pm *see below for more information on how to communicate with us in the communication policy section and how office hours and tutorials work 1
August 2022 Course Objectives, Description, and Format This course serves as an introduction to statistical concepts necessary to describe and understand data from psychological research. By the end of the course students will be able to: · use descriptive statistics to summarize and visualize data · describe, calculate, and interpret introductory inferential statistics, such as t-tests, correlations, and chi square · define p-hacking, open science, and identify bad statistical practices All course topics are listed in the course schedule and learning objectives are described in detail in Mindtap, per chapter. This class will take place in person, but I redesigned it to be flexible and accommodating for the unique challenges all of us are facing. I understand that we are still living through a pandemic and that moving to the "new normal" is a slow and complex process. Learning is an active process that requires engagement, attention, feedback, and motivation. This class is designed around that fact and requires regular and active participation. The course is organized on myCourses by week. Each week there will be a mix of lecture, practice problems with demonstration, interactive questions for participation, tutorials, and homework. All in-person lectures will be recorded so that students can review as needed. We will offer multiple office hour and tutorial times and many of the graded components have flexibility worked in to accommodate short-term illness or crisis (this is highlighted because it s a frequently asked question!). Per McGill policy, there is a general expectation that most learning activities take place in person. Occasionally course materials or a lecture may take place virtually to accommodate an emergency, bad weather,