Students

PSYH4418 – Design and Statistics IV

2023 – Session 2, In person-scheduled-weekday, North Ryde

General Information

Download as PDF
Unit convenor and teaching staff Unit convenor and teaching staff Unit Convenor, lecturer and tutor
Naomi Sweller
Contact via Email
AHH 3.501
By appointment
Credit points Credit points
10
Prerequisites Prerequisites
Corequisites Corequisites
PSYH490 or PSHY4490 or PSYH495 or PSYH4495 or PSYH4491 or PSYH4492
Co-badged status Co-badged status
Unit description Unit description

This unit is designed as preparation for honours projects and to help equip students for research careers. The unit focuses on practical issues of quantitative data analysis. Most topics are dealt with in the context of Stata. Topics include sample size and statistical power analysis, data management in Stata and more advanced methods specifically applicable to research in psychology.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Make connections between principles of good research design and relevant research questions, and correctly apply designs to the appropriate question.
  • ULO2: Demonstrate an understanding of how abstract concepts are operationalised in statistical terms in psychological research.
  • ULO3: Apply and interpret advanced statistical methods to research in psychology.
  • ULO4: Demonstrate an enhanced practical understanding of statistical software used in psychological research, with a focus on understanding the syntax required to carry out analyses and interpreting output.

General Assessment Information

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.

Quiz

The Quiz is designed to give you early feedback on your understanding of key concepts from the initial parts of the unit. The Quiz will be conducted through iLearn and will be a mixture of multiple choice and short answer questions. The Quiz will be made available at 9am on Friday 1st September, and will close at 11.55pm on Friday 8th September. The Quiz is not timed, but all responses will be automatically submitted at 11.55pm Friday 8th September. No late submissions will be permitted unless special consideration has been granted. Results will be released at 5pm on Friday 15th September and no further submissions will be accepted after the results are returned and feedback is released.

Research proposal form information

The Research Proposal Form is designed to help you with the process of planning your empirical project. It consists of a series of short answer questions, to which you will be required to write a response. Responses may include Stata syntax. The questions contained in the form will be made available in Week 1. All submissions are to be through Turnitin in iLearn. Please contact Naomi Sweller via email if your Honours project involves analysis using a topic covered after the mid-session break. An alternate due date will be discussed.

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:

Number of days (hours) late Total Possible Marks Deduction Raw mark Final mark
1 day (1-24 hours) 100 5 75 70
2 days (24-48 hours 100 10 75 65
3 days (48-72 hours) 100 15 75 60
7 days (144-168 hours) 100 35 75 40
>7 days (>168 hours) 100 - 75 0

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. 

Final examination information

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, in line with the Assessment Policy and Procedure.

This will be a 2-stage exam, with a team-work component. The exam will be a mixture of multiple choice and “fill in the blank” short answer questions. The procedure is such that you will first sit the exam individually, and then immediately afterwards in the same time slot you will do the exam again in groups of approximately four. The exams will then be graded such that 90% of the score comes from the individual attempt, and 10% from the group attempt, unless the individual attempt is better than the group attempt, in which case the student will get 100% of their score from the individual attempt.

The Unit Convenor will be allocating all students to groups. The group allocations will be posted to iLearn in the week prior to the exam. All allocations will be completely random and based on a random number generator.

If a student misses the exam due to illness or other unavoidable circumstances they can sit a supplementary exam which will contain only an individual component, with no group component. If a student has special circumstances such as the need for a longer testing time, they will sit the individual exam at the same time as the rest of the group, but they may start the exam earlier to enable them to finish the individual component with enough time to commence the group component with the rest of their group.

Students who are unable to sit an examination must submit an Application for Special Consideration form (supporting documentation from a medical or health care professional clearly stating the reasons for the absence from the exam must be attached to your submission). 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.

If a Supplementary Examination is granted as a result of the Special Consideration process, the examination will usually be held one week after the original examination date. 

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.

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.

Fit to sit model

Students who sit an exam and/or in-class test or otherwise submit an assessment, declare themselves fit to do so and will not be eligible to apply for special consideration unless there is evidence that (a) they were unfit to make reasonable judgement on their fitness to undertake the assessment, due to mental illness or other exceptional circumstances; or (b) they were taken ill during the assessment (in the case of an examination or test), and this can be independently corroborated.

Assessment Tasks

Name Weighting Hurdle Due
Quiz 10% No 11:55pm Friday 8th September (Week 7)
Plan (Research): Research Proposal Form 35% No 11:55pm Friday 29th September (Week 8)
Final Examination 55% No In class Thursday 2nd November (Week 13)

Quiz

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 10 hours
Due: 11:55pm Friday 8th September (Week 7)
Weighting: 10%

 

The quiz will be held online and will assess material covered in the early stages of the unit.

 


On successful completion you will be able to:
  • Make connections between principles of good research design and relevant research questions, and correctly apply designs to the appropriate question.
  • Demonstrate an understanding of how abstract concepts are operationalised in statistical terms in psychological research.
  • Apply and interpret advanced statistical methods to research in psychology.
  • Demonstrate an enhanced practical understanding of statistical software used in psychological research, with a focus on understanding the syntax required to carry out analyses and interpreting output.

Plan (Research): Research Proposal Form

Assessment Type 1: Plan
Indicative Time on Task 2: 44 hours
Due: 11:55pm Friday 29th September (Week 8)
Weighting: 35%

 

The Research Proposal Form is designed to help you with the process of planning your empirical project. No word limit required.

 


On successful completion you will be able to:
  • Make connections between principles of good research design and relevant research questions, and correctly apply designs to the appropriate question.
  • Demonstrate an understanding of how abstract concepts are operationalised in statistical terms in psychological research.
  • Apply and interpret advanced statistical methods to research in psychology.
  • Demonstrate an enhanced practical understanding of statistical software used in psychological research, with a focus on understanding the syntax required to carry out analyses and interpreting output.

Final Examination

Assessment Type 1: Examination
Indicative Time on Task 2: 50 hours
Due: In class Thursday 2nd November (Week 13)
Weighting: 55%

 

Final examination held in scheduled class time, in accordance with relevant requirements.

 


On successful completion you will be able to:
  • Make connections between principles of good research design and relevant research questions, and correctly apply designs to the appropriate question.
  • Demonstrate an understanding of how abstract concepts are operationalised in statistical terms in psychological research.
  • Apply and interpret advanced statistical methods to research in psychology.
  • Demonstrate an enhanced practical understanding of statistical software used in psychological research, with a focus on understanding the syntax required to carry out analyses and interpreting output.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

As a student enrolled in this unit, you will engage in a range of online and face to face learning activities, including readings, videos and live Q&A sessions. Details can be found on the iLearn site for this unit.

Textbooks

There are two textbooks for this unit, both available through the Library:

Tabachnick, B., & Fidell, L. (2019). Using Multivariate Statistics (7th ed.). New York, NY: Pearson.

Keith, T. Z. (2019). Multiple regression and beyond: an introduction to multiple regression and structural equation modeling (3rd ed.). New York, NY: Routledge.

Please note that the previous editions of the textbooks will be acceptable for use in this unit. Page numbers may differ from those noted for the most recent editions, and you should check carefully with the library holdings of the prescribed editions that the content is equivalent.

Additional reading

There is an additional reading for the week on power and sample size:

Lachin, J. M. (1981). Introduction to sample size determination and power analysis for clinical trials. Controlled Clinical Trials, 2, 93-113.

Classes

Thirteen weeks: 12 x 2-hour lecture and 1-hour demonstration, with final examination held in the Week 13 lecture slot. There will be no live lectures or demonstrations for this unit. Instead, you will be given access to the recordings of the Session 1 offering of this unit, and in addition will be offered a Q&A session held live with the Unit Convenor. This live session will be held during the timetabled class scheduled for this session, and will typically take 1 hour.

The recordings you will be given access to will involve:

  1. Lectures involving demonstrations of Stata procedures, using various examples. Students are encouraged to bring their own laptop with Stata installed, but this is not required. Theoretical issues will also be discussed during the lectures.
  2. Practical exercises set each week for students to undertake in their own time. The following week there will be a demonstration session in addition to the lecture in which the lecturer will show (live) how they would approach the exercises. Students are encouraged to bring their own laptop computers to demonstration sessions to follow along. Questions are encouraged during this session in particular.

This version of the unit is “In person scheduled weekday”. 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

Technology Used

Active participation in the learning activities throughout the unit will require students to have access to a tablet, laptop or similar device. Students who do not own their own laptop computer may borrow one from the university library.

Unit Schedule

Week Lecture topic Required reading
1

Introduction to unit, Research Ethics, Data manipulation in Stata

TBA
2

Introduction to sample size and statistical power analysis

Tabachnick & Fidell, sections 1.5, 3.1.2.

Lachin journal article

3

Interactions in regression (including categorical and continuous predictors)

Tabachnick & Fidell, section 5.6.6

Keith, Chapters 7 & 8

4

Advanced Logistic Regression #1

Keith, Chapter 11 (logistic regression section only)

Tabachnick & Fidell, Chapter 10

5

Advanced Logistic Regression #2

Tabachnick & Fidell, Chapter 10
6

MANOVA

Tabachnick & Fidell, Chapter 7
7

Multi-Level Modelling

Tabachnick & Fidell, Chapter 15
8

Path Analyses with Regression

Keith, Chapters 12 &13

Tabachnick & Fidell, section 5.6.7

9

Path Analyses through SEM

Keith, Chapter 14

Tabachnick & Fidell, Chapter 14 (this chapter is optional and includes much more detail than needed)

10

Exploratory Factor Analysis #1

Tabachnick & Fidell, Chapter 13
11

Exploratory Factor Analysis #2

Tabachnick & Fidell, Chapter 13
12

Confirmatory Factor Analysis

Keith, Chapter 16
13

Final examination

 

 

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

The Writing Centre

The Writing Centre provides resources to develop your English language proficiency, academic writing, and communication skills.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via AskMQ, or contact Service Connect.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Inclusion and Diversity

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.

Professionalism

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.


Unit information based on version 2023.01R of the Handbook