Grade descriptors and other information concerning grading are contained in the Macquarie University Assessment Policy.

All final grades are determined by a grading committee, in accordance with the Macquarie University Assessment Policy, and are not the sole responsibility of the Unit Convenor.

Students will be awarded a final grade and a mark which must correspond to the grade descriptors specified in the Assessment Procedure (clause 128).

To pass this unit, you must demonstrate sufficient evidence of achievement of the learning outcomes, meet any ungraded requirements, and achieve a final mark of 50 or better.

Further details for each assessment task will be available on iLearn.

Late Submissions

Unless a Special Consideration request has been submitted and approved, a 5% penalty (OF THE TOTAL POSSIBLE MARK) will be applied each day a written assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted. Submission time for all written assessments is set at 11.55pm. A 1-hour grace period is provided to students who experience a technical concern. 

 For example:

For any late submissions of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, students need to submit an application for Special Consideration.

No further submissions will be accepted after the marked assignments are returned and feedback is released to students.

The final exam for this unit is scheduled to occur on Macquarie University campus. Students are expected to make themselves available for the final exam, at the date and time set by the University, in line with the Assessment Policy and Procedure.

 Word count penalty: 5% of the possible mark will be deducted per 100 words over the word limit for the assessment task. An additional 99 words beyond the limit can be written without penalty.

Sitting the final exam is compulsory in order to be eligible to pass the unit. Any student who does not attempt the final exam will be granted a Fail Absent grade.

Examination Policy

You are expected to present yourself for examination at the time and place designated in the University Examination Timetable. The timetable will be available in Draft form approximately eight weeks before the commencement of the examinations and in Final form approximately four weeks before the commencement of the examinations and will be available from this website: http://students.mq.edu.au/student_admin/exams

The only exception to not sitting an examination at the designated time is because of documented illness or unavoidable disruption. In these circumstances you should apply for Special Consideration, through https://ask.mq.edu.au. If a Supplementary Examination is granted as a result of the Special Consideration process, the examination will be scheduled after the conclusion of the official examination period. An email will be sent to the student advising them of the outcome of their request for a supplementary exam. If a supplementary exam has been granted, it is the student’s responsibility to check the date and location of the supplementary exam although they are generally in mid-July. Students who are granted to sit for a supplementary exam must make themselves available to sit for the supplementary exam on the specified date. There will only be one time. You are advised that it is Macquarie University policy not to set early examinations for individuals or groups of students. All students are expected to ensure that they are available until the end of the teaching semester, which is the final day of the official examination period.

The final exam for this unit is currently scheduled to occur on Macquarie University campus. Students are expected to make themselves available for the final exam, at the date and time set by the University, in line with the Assessment Policy and Procedure. Sitting the final exam is compulsory in order to be eligible to pass the unit. Any student who does not attempt the final exam will be granted a Fail Absent grade.

Weekly online quizzes

12 practical quizzes will be worth 1% each to a maximum overall value of 10% across the session. Only the best 10 quizzes from each student will contribute to the final score out of 10. The two quizzes with the lowest scores across the session will be discounted from each student's mark.

The unit’s practical program is vital for students to have a first-hand understanding of the material and its application in psychology research. Each week (starting week 1) there will be a set of practical tasks to complete. Most weeks this will involve a simple, practical data analysis (involving Stata) and interpretation task, although some weeks students may be given Stata output to interpret and asked to answer some questions using the output. The requirement to complete a small online quiz each week will help ensure that students keep up with the unit material week-by-week. Tutors will then work through the solution during practical classes in the subsequent week. Solutions to quizzes will not be made available outside of practical classes. The final task, which students complete in Week 13, will be graded but will not be reviewed in practical classes. The answers will be posted on iLearn instead. Quizzes must be completed within iLearn by 5pm on the Friday before the week in which it will be discussed. The one exception to this rule is the quiz for Week 1 which must be submitted via iLearn by 5pm on Sunday 26th February. The iLearn quiz will not accept submissions after the deadline and a mark of zero for that week will be recorded if no quiz is submitted on-time. Each quiz is completed via iLearn and you will receive your mark once the quiz closes.

The quizzes must be completed individually by each student. If there are technical problems associated with iLearn (e.g., error message and then being unable to complete the quiz), make sure you take a screen shot of any error messages that occur. If a screen shot of an error occurring within iLearn is sent to Erik Reichle before the quiz deadline, and it is deemed to be an error occurring that was out of the student’s control, then a second attempt at the quiz will be granted, as long as the quiz attempt was commenced at least 2 hours before the quiz deadline and must be completed before the first practical class that reviews the quiz. No second attempts will be granted if you begin your attempt too late and cannot complete the quiz before 5pm Friday. It is strongly recommended you complete your quiz well in advance of the 5pm deadline! In the event of health or other issues that may prevent you from completing the quiz by the 5pm deadline, you may apply for Special Consideration to be exempted from 1 quiz only. If further issues are experienced that warrant special consideration, an alternate assessment task will be set to replace the missed quiz(zes).

Midsession Practical Exam

PSYU3349 is a unit emphasising practical data analysis for psychologists and hence an assessment on practical data analysis is crucial. This is a one-hour computer-based test conducted on campus, which will cover the content from Weeks 1 – 4 of the unit. The test will involve “live” analysis of datasets in Stata, and students will be required to answer questions relating to their analyses. Questions will be a combination of fill in the blank-style numeric entry questions and multiple choice questions. The test will be conducted entirely through iLearn. No internet access is allowed during this exam and any attempt to do so will be considered cheating. Separate laptops / tablets / mobile phones will not be permitted. The test is closed book and no external written or electronic materials will be permitted. Students are required to enrol in one of the exam "class" slots on eStudent in the same manner as you enrol in other unit classes. Students will only be permitted to sit the test in the slot in which they are enrolled and must bring their student ID to the exam room for verification. If you do not enrol in one of the slots or you do not bring your student ID you will not be eligible to sit the test. Similarly, if you miss your timeslot you will not be permitted to sit the test in the subsequent slot. 

Practical project

In the practical project, students are asked to address a practical research question and must operationalise it and determine an appropriate course of analysis with only general directions. Stata commands needed to complete the practical project will not be provided for you. You will be expected to have learnt the required Stata commands through understanding the demonstration programs used in lectures, quizzes, and practical classes, and through your own practice with Stata. Details of the practical project including the question and the dataset will be made available via iLearn.

Please also note that iLearn can lag when large numbers of students are in the system at the same time. Submission time for assignments will be counted as the time the assessment was received. Because of this, make sure you don't leave your submission minutes before is due! Late penalties will be strictly applied to assignments that are received after the due time.

Lectures

There are three hours of lectures per week. These lectures will take place on campus (Thursdays 6-9 pm), and recordings will be available via Echo360 on iLearn after the lecture has concluded.

Students can enroll in either an on-campus lecture (space permitting) or an online/live-streamed lecture classes. Students should not attend on-campus classes if you are unwell or have any cold and flu-like symptoms.

For general information on unit versions, see this website https://students.mq.edu.au/study/enrolling/choosing-units

Practical Classes

There is a one hour practical class each week, starting in Week 2. You must attend the class you are enrolled in. Official changes to all classes can be done online via eStudent. If you cannot attend your scheduled class for a particular week, you may attend an alternate class as a make-up provided: 1) for on-campus classes there are spare seats after all students enrolled in that class have taken their seats and 2) for on-line classes students understand that those enrolled in the class will have priority when asking questions during class. Please email the tutor of the class you wish to attend for a particular week to check.

In Person Scheduled Attendance Pattern: Students can enroll in either an on-campus lecture (space permitting) or an online/live-streamed lecture classes. This version of the unit has on-campus practical classes only. Students should not attend on-campus classes if you are unwell or have any cold and flu-like symptoms. Ensure you follow the most recent University COVID-19 advice https://www.mq.edu.au/about/coronavirus-faqs/information-for-students For general information on unit versions, see this website https://students.mq.edu.au/study/enrolling/choosing-units

Online Scheduled In-Person Attendance Pattern:  Students can live-stream the lecture (via Echo in iLearn) or watch the lecture recording later in the week. Practical classes run online via zoom. Note that enrolment in online classes does not mean that the entire unit will be taken online: The mid-session exam and the final exam will both take place on Macquarie University campus. 

For general information on unit versions, see this website https://students.mq.edu.au/study/enrolling/choosing-units

Textbook

Agresti, A. (2018). Statistical Methods for the Social Sciences (5thed.). Boston, USA: Pearson.

Additional weekly readings are available through Leganto on iLearn.

Computing

You are expected to have had prior experience in the use of Stata before coming into PSYU3349, and be able to read raw data files, access pre-existing data files and retrieve Stata data files. You are also expected to have some knowledge of syntax in Stata. You can directly download Stata to your own computer from MQ's website https://students.mq.edu.au/support/technology/software/stata following the instructions closely. If you experience technical issues, contact IT Help https://students.mq.edu.au/support/technology/service-desk

Competent use of Stata is required heading into PSYU3349. If you need a refresher on Stata, then this playlist offers a good place to start: https://www.youtube.com/playlist?list=PLN5IskQdgXWnnIVeA_Y0OBGmnw21fvcmU

There are three hours of lectures each week. The lectures are considered essential to understanding the unit material so you must access the recordings online. The lecture content will begin by building on PSYU2248 statistical modelling, with special reference to the General Linear Model (GLM). The GLM includes regression models (simple and multiple), the t-test, oneway ANOVA models, factorial ANOVA models (balanced and unbalanced), ANCOVA models and models involving statistical control with mixed measurement independent variables. For these models we will only concern ourselves with models which have one, numeric dependent variable. Following this, we will cover approaches to analysis of non-Normal dependent variables including bootstrapping and Logistic Regression (categorical DV). As our models become more complex (i.e., have increasing numbers of independent variables), we will discuss the process of model reduction. The unit finishes with an extension of ANOVA content into repeated measures and mixed within/between subject designs. 

Social inclusion at Macquarie University is about giving everyone who has the potential to benefit from higher education the opportunity to study at university, participate in campus life and flourish in their chosen field. The University has made significant moves to promote an equitable, diverse and exciting campus community for the benefit of staff and students. It is your responsibility to contribute towards the development of an inclusive culture and practice in the areas of learning and teaching, research, and service orientation and delivery. As a member of the Macquarie University community, you must not discriminate against or harass others based on their sex, gender, race, marital status, carers' responsibilities, disability, sexual orientation, age, political conviction or religious belief. All staff and students are expected to display appropriate behaviour that is conducive to a healthy learning environment for everyone.

In the Faculty of Medicine, Health and Human Sciences, professionalism is a key capability embedded in all our courses.

As part of developing professionalism, students are expected to attend all small group interactive sessions including clinical, practical, laboratory, work-integrated learning (e.g., PACE placements), and team-based learning activities. Some learning activities are recorded (e.g., face-to-face lectures), however you are encouraged to avoid relying upon such material as they do not recreate the whole learning experience and technical issues can and do occur. As an adult learner, we respect your decision to choose how you engage with your learning, but we would remind you that the learning opportunities we create for you have been done so to enable your success, and that by not engaging you may impact your ability to successfully complete this unit. We equally expect that you show respect for the academic staff who have worked hard to develop meaningful activities and prioritise your learning by communicating with them in advance if you are unable to attend a small group interactive session.

Another dimension of professionalism is having respect for your peers. It is the right of every student to learn in an environment that is free of disruption and distraction. Please arrive to all learning activities on time, and if you are unavoidably detained, please join activity as quietly as possible to minimise disruption. Phones and other electronic devices that produce noise and other distractions must be turned off prior to entering class. Where your own device (e.g., laptop) is being used for class-related activities, you are asked to close down all other applications to avoid distraction to you and others. Please treat your fellow students with the utmost respect. If you are uncomfortable participating in any specific activity, please let the relevant academic know.