CQUniversity Unit Profile
PSYC12047 Introduction to Data Analysis
Introduction to Data Analysis
All details in this unit profile for PSYC12047 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 introduce you to preliminary concepts in statistics. The material covered in this unit will allow you to do research as part of your undergraduate and/or professional career/s. The goal of this unit is to provide you with the skills to perform basic statistical analyses (e.g., t-tests, ANOVA, chi-square, linear regression, etc.), as they apply in the health, human, and social sciences. It is a recommendation of enrolment in the unit that you have competency at secondary-level mathematics. Students lacking competency at secondary level (including basic algebra) are encouraged to contact the Academic Learning Centre (ALC) to discuss their options before enrolling in this unit.

Details

Career Level: Undergraduate
Unit Level: Level 2
Credit Points: 6
Student Contribution Band: 7
Fraction of Full-Time Student Load: 0.125

Pre-requisites or Co-requisites

There are no requisites for this unit.

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. Online Quiz(zes)
Weighting: 40%
2. Portfolio
Weighting: 50%
3. Written Assessment
Weighting: 10%

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 Student evaluation.

Feedback

Students reported that, despite finding it interesting and useful, lecture content could be condensed and 'filler content' reduced.

Recommendation

The Unit Coordinator intends to modularise the unit into shorter conceptual videos, with 'need to know' content highlighted first, and additional modules for extended/further study also being made available. Weekly lectures might, instead, follow the 'flipped classroom' model, where content will be recapped and discussed (with a focus on applications and example calculations).

Feedback from Student evaluation and Personal communication.

Feedback

Students really liked the support of on-campus tutors and the availability of practice tasks for each assessment on the Moodle site. The majority of students reported liking the frequent (near-weekly) assessment schedule, but this was not the case for all students (especially for students who reported having competing extra-curricular commitments).

Recommendation

The current model of on-campus support, provision of comprehensive preparation materials, and assessment schedule should be continued.

Feedback from Student evaluation.

Feedback

Support for the Computer Assessment Task could be improved.

Recommendation

More examples for this assessment should be provided in the next iteration of the unit. Task expectations should be incorporated into lecture/tutorial materials earlier in the term, in order to improve communication of these.

Feedback from Student evaluation and Personal communication.

Feedback

Some students reported not needing the textbook, whereas others report highly valuing this (noting that they particularly like the simplicity of readings).

Recommendation

Review alternate options for textbook, as well as the appropriateness of an annotated study guide for this unit.

Unit Learning Outcomes
On successful completion of this unit, you will be able to:
  1. Explain and evaluate different statistical methods and procedures
  2. Apply statistical procedures, methods and calculations
  3. Translate statistical output into a summary, formatted in APA style.
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 - Online Quiz(zes) - 40%
2 - Portfolio - 50%
3 - Written Assessment - 10%

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
10 - Aboriginal and Torres Strait Islander Cultures

Alignment of Assessment Tasks to Graduate Attributes

Assessment Tasks Graduate Attributes
1 2 3 4 5 6 7 8 9 10
1 - Online Quiz(zes) - 40%
2 - Portfolio - 50%
3 - Written Assessment - 10%
Textbooks and Resources

Textbooks

Prescribed

Understanding Statistics in Psychology with SPSS

8th Edition (2020)
Authors: Howitt, D., & Cramer, D.
Pearson
Harlow Harlow , Essex , UK
ISBN: 9781292282305
Binding: Paperback
Supplementary

Publication Manual of the American Psychological Association

7th Edition (2020)
Authors: American Psychological Association
American Psychological Association
Washington Washington , DC , USA
ISBN: 9781433832161
Binding: Paperback

Additional Textbook Information

Due to availability issues, students preferring a paper copy can purchase the previous 7th edition at the CQUni Bookshop here: http://bookshop.cqu.edu.au (search on the Unit code).

Alternatively, an eBook version of the 8th edition can be purchased at the publisher’s website: https://www.pearson.com.au/9781292282336

IT Resources

You will need access to the following IT resources:
  • CQUniversity Student Email
  • Internet
  • Unit Website (Moodle)
  • GNU PSPP (free statistics analysis program)
Referencing Style

All submissions for this unit must use the referencing style: American Psychological Association 7th Edition (APA 7th edition)

For further information, see the Assessment Tasks.

Teaching Contacts
Lisa Lole Unit Coordinator
l.lole@cqu.edu.au
Schedule
Week 1 Begin Date: 13 Jul 2020

Module/Topic

Introduction to Data Analysis

Chapter

1 and 2

Events and Submissions/Topic

Week 2 Begin Date: 20 Jul 2020

Module/Topic

Describing our Variables

Chapter

3, 4, and 5

Events and Submissions/Topic

Week 3 Begin Date: 27 Jul 2020

Module/Topic

Z-scores, Percentiles, & Probability

Chapter

6, 10, and 19

Events and Submissions/Topic

Online Quiz Due: Week 3 Thursday (30 July 2020) 9:00 am AEST
Week 4 Begin Date: 03 Aug 2020

Module/Topic

Data Relationships &

Reporting Our Results

Chapter

7 and 15

Events and Submissions/Topic

Calculation Portfolio Due: Week 4 Thursday (6 Aug 2020) 9:00 am AEST
Week 5 Begin Date: 10 Aug 2020

Module/Topic

Hypothesis testing 

Chapter

12 and 20

Events and Submissions/Topic

Online Quiz (#2) DUE: Week 5 Thursday (13 Aug. 2020) 9:00 am AEST

Vacation Week Begin Date: 17 Aug 2020

Module/Topic

-

Chapter

-


Events and Submissions/Topic

-

Week 6 Begin Date: 24 Aug 2020

Module/Topic

Correlation

Chapter

8 and 11

Events and Submissions/Topic

Online Quiz (#3) DUE: Week 6 Thursday (27 Aug. 2020) 9:00 am AEST

Week 7 Begin Date: 31 Aug 2020

Module/Topic

Simple regression &

Partial correlation

Chapter

9 and 32

Events and Submissions/Topic

Calculation Portfolio Task (#2) DUE: Week 7 Thursday (3 Sept. 2020) 9:00 am AEST

Week 8 Begin Date: 07 Sep 2020

Module/Topic

Related samples t-test

Chapter

13

Events and Submissions/Topic

Online Quiz (#4) DUE: Week 8 Thursday (10 Sept. 2020) 9:00 am AEST

Week 9 Begin Date: 14 Sep 2020

Module/Topic

Unrelated samples t-test

Chapter

14

Events and Submissions/Topic

Calculation Portfolio (#3) DUE: Week 9 Thursday (17 Sept. 2020) 9:00 am AEST

Week 10 Begin Date: 21 Sep 2020

Module/Topic

Chi-square 

Chapter

18

Events and Submissions/Topic

Calculation Portfolio Task (#4) DUE: Week 10 Thursday (24 Sept. 2020) 9:00 am AEST

Week 11 Begin Date: 28 Sep 2020

Module/Topic

Independent groups ANOVA

Chapter

22, 23, and 25

Events and Submissions/Topic

Calculation Portfolio Task (#5) DUE: Week 11 Thursday (1 Oct. 2020) 9:00 am AEST

Week 12 Begin Date: 05 Oct 2020

Module/Topic

Effect size &

Confidence intervals 

Chapter

16 and 17

Events and Submissions/Topic

Computer Task Due: Week 12 Friday (9 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 Online Quiz(zes)

Assessment Title
Online Quiz

Task Description

You will be required to complete four Online Quizzes.

These are comprised of 20 multiple-choice questions and you will have 25 minutes to answer these. 

You have one attempt at each quiz.

  • Quiz 1 (due in Week 3) will cover material from Weeks 1 and 2
  • Quiz 2 (due in Week 5) will cover material from Weeks 3 and 4
  • Quiz 3 (due in Week 6) will cover material from Week 5
  • Quiz 4 (due in Week 8) will cover material from Weeks 6 and 7


Number of Quizzes

4


Frequency of Quizzes

Other


Assessment Due Date

Week 3 Thursday (30 July 2020) 9:00 am AEST

Quiz #2 is due 9 am (AEST) on 13/08/2020; Quiz #3 is due 9 am (AEST) on 27/08/2020; Quiz #4 is due 9 am (AEST) on 10/09/2020


Return Date to Students

Week 8 Thursday (10 Sept 2020)

Grades and feedback will be made available in Moodle immediately after each quiz closes (see DUE dates above).


Weighting
40%

Assessment Criteria

Each correct answer will be awarded half (0.5) a mark.


Referencing Style

Submission
Online

Submission Instructions
These timed quizzes are to be taken via the Moodle site.

Learning Outcomes Assessed
  • Explain and evaluate different statistical methods and procedures
  • Translate statistical output into a summary, formatted in APA style.


Graduate Attributes
  • Problem Solving
  • Information Literacy

2 Portfolio

Assessment Title
Calculation Portfolio

Task Description

You will be required to complete five Calculation Portfolio tasks.

You have one attempt for each Calculation Portfolio task, for which you will have 2 hours to complete it.

You have one attempt at each task.

  • Portfolio 1 (due Week 4) will cover material from Weeks 1, 2, and 3
  • Portfolio 2 (due Week 7) will cover material from Weeks 6
  • Portfolio 3 (due Week 9) will cover material from Week 8
  • Portfolio 4 (due Week 10) will cover material from Week 9
  • Portfolio 5 (due Week 11) will cover material from Week 10


Assessment Due Date

Week 4 Thursday (6 Aug 2020) 9:00 am AEST

Calculation task #2 is due 9 am (AEST) on 03/09/2020; Calculation task #3 is due 9 am (AEST) on 17/09/2020; Calculation task #4 is due 9 am (AEST) on 24/09/2020; Calculation task #5 is due 9 am (AEST) on 01/10/2020


Return Date to Students

Week 11 Thursday (1 Oct 2020)

Grades and feedback will be made available in Moodle immediately after each task closes (see DUE dates above).


Weighting
50%

Assessment Criteria

Each correct answer will be awarded one (1) mark.


Referencing Style

Submission
Online

Submission Instructions
These timed calculation tasks are to be taken via the Moodle site.

Learning Outcomes Assessed
  • Apply statistical procedures, methods and calculations


Graduate Attributes
  • Problem Solving
  • Information Technology Competence

3 Written Assessment

Assessment Title
Computer Task

Task Description

You will be required to choose and run an appropriate statistical analysis using computer-based software, as well as interpret and report these results in American Psychological Association (APA) format.


Assessment Due Date

Week 12 Friday (9 Oct 2020) 11:55 pm AEST


Return Date to Students

Exam Week Friday (23 Oct 2020)

Assessments with feedback will be returned approximately two weeks from the due date.


Weighting
10%

Assessment Criteria

This assessment will be graded out of 10. Marks will be allocated, according to the following criteria:

          1. Selection of an appropriate statistical analysis for the given data (2 marks)
          2. Justification for the choice of statistical test (2 marks)
          3. Results reported and interpreted correctly (4 marks)
          4. Results written according to American Psychological Association (APA) standards (2 marks)


          Referencing Style

          Submission
          Online

          Submission Instructions
          Students will upload a Word document with their submission to the Moodle site.

          Learning Outcomes Assessed
          • Explain and evaluate different statistical methods and procedures
          • Apply statistical procedures, methods and calculations
          • Translate statistical output into a summary, formatted in APA style.


          Graduate Attributes
          • Communication
          • 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?