• 4 Assignments (each worth 10%): 40%
• Midterm Exam: 30%
• Final Exam: 30%

NOTES:

Office hours

Fridays, 12-1, RCB4202

Though optional, regular participation in the office hours is highly recommended. It is expected that, among other things, students will use this time to discuss matters related to the filmed lectures, the readings, workouts, and assignments. That is to say, anything whatsoever statistical or data analytic is fair game.

REQUIREMENTS:

Components of course

Lectures and lecture notes

Lectures, and the lecture notes on which they are based, are the primary means by which will be covered, the materials of which the course is comprised. The lectures are structured sequentially in accordance with the lecture notes, and proceed through the theoretical materials in a linear fashion, with occasional departures to address computational and output-interpretational issues. The midterm and final are, almost exclusively- Kirk’s chapters on research design being the exception-, based on the lectures. In each lecture, I will be referring directly to the accompanying lecture notes. However, the notes comprise but a sketch. Accordingly, elucidation, fleshing out, and expanding upon will be the standard order of business.

Note: lecture notes will be available on Canvas, in accordance with lecture schedule.

Assignments

Each of the four assignments will be constituted of either one or two parts, the parts made available to you- on Canvas- as the semester unfolds. A given assignment- all of its parts- will be due- uploaded to Canvas- on the date and time specified on the schedule, below. The majority of the assignments involve the addressing of empirical questions by means of data and statistical analysis.  Computations may be carried out in either SPSSX or R. When addressing an empirical question by means of data and statistical analysis, your answers must conform to the following structure: i. Introduction; ii. data analysis; iii. statement of statistical hypothesis to be tested; iv. error analysis (power computations and choice of type I error rate); v. assumption checking; vi. outcome of hypothesis test; vii. (wherein necessary) magnitude of effect estimate. The document examplesassign.pdf, available to you in the first module of Canvas, is an assignment from the past which exemplifies this proper structuring.

Midterm and final

There will be one midterm- in class- and one take-home final. You will be able to access the final on Canvas, and will be required to upload your completed exam to Canvas, in accordance with the course schedule. The final is not cumulative.  Neither midterm, nor final, will involve any computation. Both test on the statistical theory on which the course focuses; both are comprised of short essay questions, true and false questions calling for detailed elaboration, etc. You will receive many examples of past midterms and finals, and, once having received these, it is urged that you practice writing out answers. You are encouraged to discuss with me these practice exams, and I will be happy, also, to offer my opinion as to the quality of your written attempts. Traditionally, we spend a lot of office time, in psyc410/910, going over peoples’ answers to practice questions.

Workouts

There will be a number of “workouts”, relatively brief computational/theoretical exercises, each of which we will tackle in the microlab (accordance with the course schedule).  Though it is highly recommended that you complete each and every workout (for they are designed to help you consolidate theoretical knowledge and master practical application), they are not for marks and you will not submit them.  Rather, there will be made available to you on Canvas, at the end of the week on which a workout is assigned, an answer key with which, at your leisure, you may compare your answers (and, of course, discuss during office hours).