CQUniversity Unit Profile
PSYC13015 Advanced Methods in Psychology
Advanced Methods in Psychology
All details in this unit profile for PSYC13015 have been officially approved by CQUniversity and represent a learning partnership between the University and you (our student).
The information will not be changed unless absolutely necessary and any change will be clearly indicated by an approved correction included in the profile.
General Information

Overview

This unit will give you the analytic skills necessary to carry out advanced applied research. There is both theory and computer 'hands-on' experiential exercises. The primary aim of the unit is to introduce you to a variety of univariate and multivariate analytic techniques (e.g., t-test, ANOVA, ANCOVA, Regression, GLM) as well as developing skills in applying appropriate analyses relevant to a specific research design. It builds on earlier units by introducing more advanced statistical techniques and requires the use of industry standard software packages such as SPSS. Online tutorial sessions allow the chance to practice core SPSS skills.

Details

Career Level: Undergraduate
Unit Level: Level 3
Credit Points: 6
Student Contribution Band: 7
Fraction of Full-Time Student Load: 0.125

Pre-requisites or Co-requisites

PSYC12047 and PSYC12048.

Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework).

Offerings For Term 2 - 2020

Adelaide
Bundaberg
Cairns
Online
Rockhampton
Townsville

Attendance Requirements

All on-campus students are expected to attend scheduled classes – in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).

Class and Assessment Overview

Recommended Student Time Commitment

Each 6-credit Undergraduate unit at CQUniversity requires an overall time commitment of an average of 12.5 hours of study per week, making a total of 150 hours for the unit.

Class Timetable

Bundaberg, Cairns, Emerald, Gladstone, Mackay, Rockhampton, Townsville
Adelaide, Brisbane, Melbourne, Perth, Sydney

Assessment Overview

1. Written Assessment
Weighting: 15%
2. Research Assignment
Weighting: 40%
3. Report
Weighting: 45%

Assessment Grading

This is a graded unit: your overall grade will be calculated from the marks or grades for each assessment task, based on the relative weightings shown in the table above. You must obtain an overall mark for the unit of at least 50%, or an overall grade of ‘pass’ in order to pass the unit. If any ‘pass/fail’ tasks are shown in the table above they must also be completed successfully (‘pass’ grade). You must also meet any minimum mark requirements specified for a particular assessment task, as detailed in the ‘assessment task’ section (note that in some instances, the minimum mark for a task may be greater than 50%). Consult the University’s Grades and Results Policy for more details of interim results and final grades.

Previous Student Feedback

Feedback, Recommendations and Responses

Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.

Feedback from Staff self-reflection, students via Moodle and email.

Feedback

Two Zoom workshops per week were positively received.

Recommendation

Maintain this level of interaction to negate the need for a residential school.

Feedback from Staff self reflection, students via Moodle and email.

Feedback

Present less analysis options, focus on need to know, versus nice to know.

Recommendation

Clearly signpost what is essential to know and provide step-by-step instructional materials for this. Identify what is nice to know (e.g. for students going on to honours) and provide some advanced extra materials for students wanting more depth.

Feedback from Staff self reflection, students via Moodle and email.

Feedback

Main textbook continues to polarize opinions, with many students really liking it, but others finding the content too detailed.

Recommendation

The main textbook will be retained as many students find it helpful for understanding statistical theory. Moreover, it is used in similar units across Australian universities. A supplemental textbook will be recommended, providing more step-by-step instructions on using SPSS.

Unit Learning Outcomes
On successful completion of this unit, you will be able to:
  1. Prepare data sets suitable for analysis in SPSS
  2. Utilise advanced working knowledge of appropriate statistical tests for analyses in SPSS
  3. Write-up the results of advanced analyses in scientific APA style.

The external accrediting body is Australian Psychology Accreditation Council (APAC). The unit fulfills one of the key foundational competencies outlined in the accreditation document for students completing a 3 year psychology degree, i.e. they will acquire a depth of understanding of underlying principles, theories and concepts in the discipline, using a scientific approach to research methods and statistics. This is a compulsory (year 3) unit required to successfully complete the course.

Alignment of Learning Outcomes, Assessment and Graduate Attributes
N/A Level
Introductory Level
Intermediate Level
Graduate Level
Professional Level
Advanced Level

Alignment of Assessment Tasks to Learning Outcomes

Assessment Tasks Learning Outcomes
1 2 3
1 - Research Assignment - 40%
2 - Written Assessment - 15%
3 - Report - 45%

Alignment of Graduate Attributes to Learning Outcomes

Graduate Attributes Learning Outcomes
1 2 3
1 - Communication
2 - Problem Solving
3 - Critical Thinking
4 - Information Literacy
5 - Team Work
6 - Information Technology Competence
7 - Cross Cultural Competence
8 - Ethical practice
9 - Social Innovation

Alignment of Assessment Tasks to Graduate Attributes

Assessment Tasks Graduate Attributes
1 2 3 4 5 6 7 8 9
1 - Research Assignment - 40%
2 - Written Assessment - 15%
3 - Report - 45%
Textbooks and Resources

Textbooks

Prescribed

Discovering Statistics using IBM SPSS Statistics 5th Edition (2017)

Authors: Andy Field
Sage
London London , UK
ISBN: 9781526419521
Binding: Paperback
Supplementary

Publication Manual of the American Psychological Association (APA) 7th Edition (2019)

Authors: American Psychological Association
American Psychological Association
Washington Washington , DC , USA
ISBN: 9781433832161
Binding: Paperback
Supplementary

SPSS Statistics: A Practical Guide 4th Edition (2018)

Authors: Peter Allen, Kellie Bennett, Brody Heritage
CENGAGE
Australia
ISBN: 9780170421140
Binding: Paperback

Additional Textbook Information

If you prefer to study with a paper copy, they are available at the CQUni Bookshop here: http://bookshop.cqu.edu.au (search on the Unit code). eBooks are available at the publisher's website.

IT Resources

You will need access to the following IT resources:
  • CQUniversity Student Email
  • Internet
  • Unit Website (Moodle)
  • IBM SPSS Statistics Graduate Pack (standard or premium) edition. Preferably the latest version 26
Referencing Style

All submissions for this unit must use the referencing styles below:

For further information, see the Assessment Tasks.

Teaching Contacts
Darren Walker Unit Coordinator
d.j.walker@cqu.edu.au
Schedule
Week 1 Begin Date: 13 Jul 2020

Module/Topic

Introduction to Statistics and SPSS 

Chapter

Field Ch 1-5

Events and Submissions/Topic

Week 2 Begin Date: 20 Jul 2020

Module/Topic

Comparison of Means T tests 

Chapter

Field Ch 10 and 7 

Events and Submissions/Topic

Minor Data Analysis assessment dataset available

Week 3 Begin Date: 27 Jul 2020

Module/Topic

Comparison of Means One-Way ANOVA part A 

Chapter

Field Ch 12 and 7

Events and Submissions/Topic

Major Data Analysis assessment dataset available
Week 4 Begin Date: 03 Aug 2020

Module/Topic

Comparison of Means One-Way ANOVA part B

Chapter

Field Ch 15 and 7

Events and Submissions/Topic

Minor Data Analysis Due: Week 4 Monday (3 Aug 2020) 11:55 pm AEST
Week 5 Begin Date: 10 Aug 2020

Module/Topic

Factorial ANOVA (Introduction)

Chapter

Field Ch 14 and 15

Events and Submissions/Topic


Vacation Week Begin Date: 17 Aug 2020

Module/Topic


Chapter

Events and Submissions/Topic

Week 6 Begin Date: 24 Aug 2020

Module/Topic

Further ANOVA (e.g. Mixed Designs)

Chapter

Field Ch 16

Events and Submissions/Topic

Week 7 Begin Date: 31 Aug 2020

Module/Topic

Categorical data

Chapter

Field Ch 19

Events and Submissions/Topic

Mini-Report assessment dataset available

Week 8 Begin Date: 07 Sep 2020

Module/Topic

ANCOVA 

Chapter

Field Ch 13

Events and Submissions/Topic

Major Data Analysis Due: Week 8 Monday (7 Sept 2020) 11:55 pm AEST
Week 9 Begin Date: 14 Sep 2020

Module/Topic

Correlation and Regression

Chapter

Field Ch 8 and 9

Events and Submissions/Topic

Week 10 Begin Date: 21 Sep 2020

Module/Topic

Bringing it all together 

Chapter

No set textbook chapter 

Events and Submissions/Topic

Week 11 Begin Date: 28 Sep 2020

Module/Topic

Mini-report preparation (Discussion writing) 

Chapter

No set textbook chapter 

Events and Submissions/Topic

Week 12 Begin Date: 05 Oct 2020

Module/Topic

Mini-report preparation (self study) 

Chapter

No set textbook chapter 

Events and Submissions/Topic

Mini-Report Due: Week 12 Monday (5 Oct 2020) 11:55 pm AEST
Review/Exam Week Begin Date: 12 Oct 2020

Module/Topic

Chapter

Events and Submissions/Topic

Exam Week Begin Date: 19 Oct 2020

Module/Topic

Chapter

Events and Submissions/Topic

Assessment Tasks

1 Written Assessment

Assessment Title
Minor Data Analysis

Task Description

You will be given a dataset that requires a one-way Analysis of Variance (ANOVA) covered in the unit.  You will be required to enter the data into SPSS, analyse it and write up concisely using APA style. 



Assessment Due Date

Week 4 Monday (3 Aug 2020) 11:55 pm AEST


Return Date to Students

Week 6 Monday (24 Aug 2020)

Within 2 teaching weeks of submission


Weighting
15%

Assessment Criteria

The % of marks awarded will be split among the following criteria : appropriate analysis, assumption testing, correct interpretation of statistical output, statistics written concisely in APA format, additional statistics, e.g. effect size, confidence intervals.


Referencing Style

Submission
Online

Learning Outcomes Assessed
  • Prepare data sets suitable for analysis in SPSS
  • Write-up the results of advanced analyses in scientific APA style.


Graduate Attributes
  • Communication
  • Information Technology Competence

2 Research Assignment

Assessment Title
Major Data Analysis

Task Description

The assessment will be provided in week 3. You will be asked to complete a series of short answer questions. You will need to enter data into SPSS, run statistical tests and interpret the output in order to find answers to these questions.


Assessment Due Date

Week 8 Monday (7 Sept 2020) 11:55 pm AEST


Return Date to Students

Week 11 Monday (28 Sept 2020)

Within 3 weeks of submission (detailed feedback)


Weighting
40%

Assessment Criteria

Each of the short answer questions will be worth a proportion of the total marks for assessment. The amount each question will be worth will be explicitly stated on the assessment. Marks will reflect the CQUniversity grades descriptor and range. For example, 4 marks out of 5 = 80%, which is a Distinction grade; whilst 3 marks out of 5 = 60% which is a Pass grade.


Referencing Style

Submission
Online

Learning Outcomes Assessed
  • Prepare data sets suitable for analysis in SPSS
  • Utilise advanced working knowledge of appropriate statistical tests for analyses in SPSS


Graduate Attributes
  • Communication
  • Problem Solving
  • Critical Thinking
  • Information Technology Competence

3 Report

Assessment Title
Mini-Report

Task Description

A synopsis of a research problem with accompanying data set (s) will be provided by week 7. You are to select the appropriate procedures from the material taught in the unit and analyse the data using SPSS. You will write up a report on the results (a skeleton outline will be given for guidance), using graphs and/or tables as required. You will also interpret and discuss the results in light of the research problem provided. The submission will thus be in the form of an abbreviated APA-style report, with a 'Results' and 'Discussion' section.


Assessment Due Date

Week 12 Monday (5 Oct 2020) 11:55 pm AEST


Return Date to Students

Exam Week Friday (23 Oct 2020)

Within 3 weeks of submission (detailed feedback)


Weighting
45%

Assessment Criteria

1. Appropriate selection and application of the relevant statistical procedures and techniques,

including any required screening and/or data pre-processing (15%)

2. Appropriate presentation and interpretation of the results, including the use of well-formatted

graphs and/or tables as required (25%)

3. Appropriate critical discussion and explanation of the results in light of the research

question (s), including an acknowledgement of any strengths and weaknesses of the analysis (50%)

4. Written expression and use of references (10%)


Referencing Style

Submission
Online

Learning Outcomes Assessed
  • Utilise advanced working knowledge of appropriate statistical tests for analyses in SPSS
  • Write-up the results of advanced analyses in scientific APA style.


Graduate Attributes
  • Communication
  • Problem Solving
  • Critical Thinking
  • Information Literacy
  • Information Technology Competence

Academic Integrity Statement

As a CQUniversity student you are expected to act honestly in all aspects of your academic work.

Any assessable work undertaken or submitted for review or assessment must be your own work. Assessable work is any type of work you do to meet the assessment requirements in the unit, including draft work submitted for review and feedback and final work to be assessed.

When you use the ideas, words or data of others in your assessment, you must thoroughly and clearly acknowledge the source of this information by using the correct referencing style for your unit. Using others’ work without proper acknowledgement may be considered a form of intellectual dishonesty.

Participating honestly, respectfully, responsibly, and fairly in your university study ensures the CQUniversity qualification you earn will be valued as a true indication of your individual academic achievement and will continue to receive the respect and recognition it deserves.

As a student, you are responsible for reading and following CQUniversity’s policies, including the Student Academic Integrity Policy and Procedure. This policy sets out CQUniversity’s expectations of you to act with integrity, examples of academic integrity breaches to avoid, the processes used to address alleged breaches of academic integrity, and potential penalties.

What is a breach of academic integrity?

A breach of academic integrity includes but is not limited to plagiarism, self-plagiarism, collusion, cheating, contract cheating, and academic misconduct. The Student Academic Integrity Policy and Procedure defines what these terms mean and gives examples.

Why is academic integrity important?

A breach of academic integrity may result in one or more penalties, including suspension or even expulsion from the University. It can also have negative implications for student visas and future enrolment at CQUniversity or elsewhere. Students who engage in contract cheating also risk being blackmailed by contract cheating services.

Where can I get assistance?

For academic advice and guidance, the Academic Learning Centre (ALC) can support you in becoming confident in completing assessments with integrity and of high standard.

What can you do to act with integrity?