There are 4 forms of assessment for PSY349: weekly quizzes, which involve data analysis via SPSS and will be submitted online through iLearn; an optional mid-session test which will be held in computer labs and will involve data analysis in SPSS; a major practical project, which will involve data analysis and communication of findings in response to a research question; and the final examination. Overall grades for the unit will be determined by adding together marks for the weekly quizzes, the practical project and the final examination. See the university policy on grading for more information.

In PSY349, we encourage students to form study groups to revise course material and practice using SPSS. However, any work you submit for assessment (quizzes and the practical project) must be your own, including computations and written expression. In recent years we have had a number of problems with students copying other students' work and submitting as their own work. Firstly, we encourage students to discuss their work with each other, and working together can be especially beneficial for statistics. All pratical projects are assessed for plagiarism via Turnitin upon submission.

It is in your interest to keep a (hard or electronic) copy of your submitted work. Firstly, to be able to produce the copy if your original goes missing, and, secondly, to be able to produce an unmarked copy in the case of requesting a re-mark. If you request a re-mark you will need to submit an unmarked copy of your work, which will be marked by a different marker, and you will receive the revised mark which may be either higher or lower than the original mark. If you wish to request a re-mark you will need to collect a Department of Psychology Application for Re-mark form from the Faculty of Human Sciences Student Office in 4 Wallys Walk (C3A) and follow its directions.

Late Penalties

Late submission of the practical report will attract a penalty of 5% of the maximum mark for every day late. In other words, the assignment is worth 38%, so a penalty of 5% x 38 = 1.9 will be applied. 1.9 marks are subtracted from whatever the student received for the report for each day late. No work can be accepted after marked project reports are handed back to students.

Requests for extensions for assignments are granted by the Faculty of Human Sciences Undergraduate Student Centre.

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.

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 may wish to consider applying 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. The format of a supplementary examination is at each unit convener’s discretion and is subject to change from the original final examination.

Supplementary Exams are only offered to students who have satisfactorily completed all other assessments for the unit and were unable to sit the final exam because of documented illness or unavoidable disruption.

All applications for supplementary exams should be submitted as a Special Consideration request, through https://ask.mq.edu.au. It is the student’s responsibility to follow the steps outlined in this website and to submit supporting documentations with the request. This must be done within five (5) working days after the exam or test date. 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. 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. It is the student’s responsibility to email Student Centre to confirm attendance at the supplementary exam.

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. 

Lectures

There are three hours of lectures per week. These lectures will be recorded via Echo360 (which captures the data projector and the lecturer’s voice) and will be available on the iLearn page following the lecture. 

Tutorials 

There is a one hour tutorial each week starting in Week 2.

Managing Classes: Official changes to all units can be done on-line via eStudent, including tutorials. Students will be allowed to informally move between tutorial classes, provided there is space available. Please email the tutor of the class you wish to attend for a particular week to check. 

Textbook

Field, A. (2017). Discovering statistics using IBM SPSS Statistics (5th ed.). London, UK: SAGE.

Please note that the previous edition of the textbook (4^th edition) will be acceptable for use in this unit. Page numbers may differ from those noted for the most recent version, but the content covered will be largely equivalent. Students with previous versions of the text can consult the 5th edition in the library reserve.

Additional Readings

The texts below are useful references. Students are not required to have or read these texts but may find them useful if they are wanting additional material beyond the textbook.

Agresti, A., & Finlay, B. (2014). Statistical Methods for the Social Sciences (4th ed.). Essex, UK: Pearson Education.

Howell, D.C. (2012). Statistical methods for psychology (8th ed.). Belmont, California: Duxbury Press. 

Keith, T. Z. (2006). Multiple regression and beyond. Boston, MA: Pearson Education.

Additional readings for Week 5 lecture:

Fox, J. (2008) Bootstrapping regression models. In Applied regression analysis and generalized linear models (2^nd ed.) (pp. 587-606). Los Angeles: Sage.

Singh, K., & Xie, M. (2008). Bootstrap: A statistical method. Unpublished manuscript, Rutgers University, USA. Retrieved from http://www. stat. rutgers. edu/home/mxie/RCPapers/bootstrap.pdf.

Computing

You are expected to have had prior experience in the use of SPSS before coming into PSY349, and be able to read raw data files, access pre-existing data files and retrieve SPSS sav files. You are also expected to have some knowledge of syntax in SPSS. There are several ways of accessing SPSS throughout this course, including purchasing the software yourself, using computers on campus or logging in to iLab. These options will be discussed in more detail during the first week of lectures.

You will also be expected to access the PSY349 unit Web Page at least weekly for unit notices and information regarding data files etc. 

If you feel you need to brush up on your use of SPSS, Chapters 4 and 5 in your textbook are a good place to start. You can additionally consult the Intro to SPSS (The Red Book) pdf written by Dr. Alan Taylor on iLearn.

Lecture ethics

In large (statistics) lectures noise can often be a problem. In the interest of your colleagues and the lecturer please remain quiet during lectures. It is impossible to learn while people around you are talking. Questions directed to the lecturer are encouraged but please keep talking between yourselves to an absolute minimum. If you wish to carry on a conversation with another student please leave the lecture. The lectures are electronically recorded using the Echo360 system and will be available on iLearn. If you wish to tape the lectures on your personal tape recorder please discuss your request with the unit chair. As a general rule, please turn off your mobile phone. It is not required but you may find it useful to bring your laptop to the lectures if you wish to follow along with the practical aspects of the unit.

Tutorial classes

Tutorial classes start in week 2 but there is an online quiz due on the Sunday of the first week of semester. There is a one 1-hour tutorial class each week. Tutorials are not compulsory but tutorial material may be assessed in the final exam. Changes to all units can be done on-line via eStudent. As a general rule students are welcome to attend a tutorial session other than the one to which they are assigned as long as there are spare seats in the alternate class. If there are no spare seats and students who are allocated a seat cannot find one the tutor will ask those not allocated to that class to leave the room.

Tutors will work through the tutorial exercises and please note that solutions to online quizzes are not available from the tutors or unit chair. If you miss a tutorial class, it is your responsibility to arrange to see another student's solution.

Use of computers and SPSS

The practical component of the unit is based on the SPSS statistical package. You will be required to use SPSS outside of class hours for approximately 15-60 minutes per week preparing material for practical classes. Some practical project tasks will require SPSS sessions. SPSS may be used interactively by tutors in practical classes to illustrate the use of the computer for statistical analysis.

Students with their own personal computers can purchase a version of SPSS from the Co-op Bookshop. If you already own a copy of SPSS and it is older than that used in lectures or tutorials do not worry, the SPSS procedures used in this unit have not changed in any meaningful way for many versions. Alternately, SPSS can be accessed for free by all students via the University’s iLab system. For more information on the iLab system, see: https://wiki.mq.edu.au/display/iLab/About. Data files for use in tutorials will available for download from the PSY349 iLearn page under “Datasets for quizzes”.

Dr Alan Taylor’s document “Introduction to IBM SPSS Statistics” which is referred to in the Practical descriptions is available from the PSY349 iLearn page under “Useful links and documents”. This document will be helpful for students unfamiliar with SPSS.