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 - 2019

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. Portfolio
Weighting: 20%
2. Written Assessment
Weighting: 40%
3. Practical Assessment
Weighting: 40%

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 Moodle, email, chats after class

Feedback

Textbook too detailed

Recommendation

Main textbook will be reviewed to see if still suitable for theoretical and practical aspects of running SPSS analyses. A supplemental 'step by step' textbook will be recommended to help with practical aspects.

Feedback from Moodle, email, chats after class

Feedback

Lecture content not focused enough

Recommendation

Produce more concise lectures that give students less data analysis options.

Feedback from Moodle, email, chats after class

Feedback

Major assignment requirements clearer

Recommendation

Produce more detailed and explicit requirements that give students less data analysis options.

Feedback from Moodle, email

Feedback

Local Tutor support helpful

Recommendation

Have a support Tutor on campuses where PSYC13015 lectures are offered by ISL

Feedback from Moodle, email, chats after class

Feedback

Unit Coordinator is enthusiastic about students grasping a difficult subject

Recommendation

Maintain Lecturer enthusiasm and time to interact live, through marking and local Tutor support

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 (level 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 - Written Assessment - 40%
2 - Portfolio - 20%
3 - Practical Assessment - 40%

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 - Written Assessment - 40%
2 - Portfolio - 20%
3 - Practical Assessment - 40%
Textbooks and Resources

Textbooks

Prescribed

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

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

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 style: American Psychological Association 6th Edition (APA 6th edition)

For further information, see the Assessment Tasks.

Teaching Contacts
Darren Walker Unit Coordinator
d.j.walker@cqu.edu.au
Schedule
Week 1 Begin Date: 15 Jul 2019

Module/Topic

Introduction to Statistics and SPSS part A

Chapter

Field Ch 1-3

Events and Submissions/Topic

Week 2 Begin Date: 22 Jul 2019

Module/Topic

Introduction to statistics and SPSS part B

Chapter

Field Ch 4-5

Events and Submissions/Topic

MINI ANALYSES Portfolio (components 1 to 3) Assessment Available

Week 3 Begin Date: 29 Jul 2019

Module/Topic

Comparison of Means part A

Chapter

Field Ch 10 and 7

Events and Submissions/Topic

Written (data analysis) Assessment Available
Week 4 Begin Date: 05 Aug 2019

Module/Topic

Comparison of Means part B

Chapter

Field Ch 12, 15  and 7

Events and Submissions/Topic

MINI DATA ANALYSES (PORTFOLIO) Due: Week 4 Monday (5 Aug 2019) 11:55 pm AEST
Week 5 Begin Date: 12 Aug 2019

Module/Topic

Factorial ANOVA (Introduction)

Chapter

Field Ch 14 and 15

Events and Submissions/Topic


Vacation Week Begin Date: 19 Aug 2019

Module/Topic


Chapter

Events and Submissions/Topic

MINI ANALYSES component 2 Due: Vacation week Monday (19 Aug. 2019) 11:55 pm AEST

Week 6 Begin Date: 26 Aug 2019

Module/Topic

Further ANOVA (e.g. Mixed Designs)

Chapter

Field Ch 16

Events and Submissions/Topic

Week 7 Begin Date: 02 Sep 2019

Module/Topic

Categorical data

Chapter

Field Ch 19

Events and Submissions/Topic

Practical (mini-report) Assessment Available


MAJOR DATA ANALYSIS ASSESSMENT Due: Week 7 Monday (2 Sept 2019) 11:55 pm AEST
Week 8 Begin Date: 09 Sep 2019

Module/Topic

ANCOVA 

Chapter

Field Ch 13

Events and Submissions/Topic

Week 9 Begin Date: 16 Sep 2019

Module/Topic

Correlation and Regression

Chapter

Field Ch 8 and 9

Events and Submissions/Topic

Week 10 Begin Date: 23 Sep 2019

Module/Topic

Bringing it all together 

Chapter

No set textbook chapter 

Events and Submissions/Topic

MINI ANALYSES component 3 Due: Week 10 Monday (23 Sep. 2019) 11:55 pm AEST

Week 11 Begin Date: 30 Sep 2019

Module/Topic

Mini-report preparation (Discussion writing) 

Chapter

No set textbook chapter 

Events and Submissions/Topic

Week 12 Begin Date: 07 Oct 2019

Module/Topic

Mini-report preparation (self study) 

Chapter

No set textbook chapter 

Events and Submissions/Topic

PRACTICAL (MINI-REPORT) ASSESSMENT Due: Week 12 Monday (7 Oct 2019) 11:55 pm AEST
Review/Exam Week Begin Date: 14 Oct 2019

Module/Topic

Chapter

Events and Submissions/Topic

Exam Week Begin Date: 21 Oct 2019

Module/Topic

Chapter

Events and Submissions/Topic

Assessment Tasks

1 Portfolio

Assessment Title
MINI DATA ANALYSES (PORTFOLIO)

Task Description

You will be given datasets for 3 statistical tests covered in the Unit. You will be required to enter the data into SPSS, analyse these data and write up their analysis in brief APA style. There will be 3 datasets. Components 1 and 2 will each be worth 5% of your total grade. The third component will be worth 10% of your total grade. 


Assessment Due Date

Week 4 Monday (5 Aug 2019) 11:55 pm AEST

Components 1, 2, and 3 are due Monday 11.55pm in weeks 4, Vacation Week, and 10 respectively.


Return Date to Students

Vacation Week Monday (19 Aug 2019)

Components 1 to 3 will be returned within two weeks of submission


Weighting
20%

Assessment Criteria

For each component the % of marks awarded will be split evenly (i.e. 1 mark each for Components 1 and 2 and 2 marks each for Component  3), among the following criteria : Appropriate analysisAssumption testingCorrect interpretation of resultsStatistics 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 Written Assessment

Assessment Title
MAJOR DATA ANALYSIS ASSESSMENT

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 7 Monday (2 Sept 2019) 11:55 pm AEST


Return Date to Students

Week 9 Friday (20 Sept 2019)

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 started on the assessment. Marks awarded will reflect the CQU 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 Practical Assessment

Assessment Title
PRACTICAL (MINI-REPORT) ASSESSMENT

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 mini-report on the results, using graphs and 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 (7 Oct 2019) 11:55 pm AEST


Return Date to Students

Exam Week Monday (21 Oct 2019)

Within 2 weeks of submission


Weighting
40%

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 tables as required (30%)
  3. Appropriate critical discussion and explanation of the results in light of the research question (s), including an acknowledgement (if required) of any strengths and weaknesses of the analysis (45%)
  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?