Skip to main content
Unit of study_

SSPS6001: Quantitative Methods in Social Sciences

Semester 1, 2024 [Normal day] - Camperdown/Darlington, Sydney

Quantitative methods are vital to social science. This unit introduces students to commonly used techniques for collecting and analysing numerical data to answer empirical questions about social, cultural, and political phenomena. It addresses the description of data with graphs and tables, descriptive statistics, statistical models, hypothesis testing, and other topics. The unit is appropriate for beginners, who will gain perspective and confidence conducting their own quantitative research and critically understanding that of others. It is taught in a computer lab, giving students practical experience with statistical software.

Unit details and rules

Unit code SSPS6001
Academic unit Sociology and Criminology
Credit points 6
Assumed knowledge


Available to study abroad and exchange students


Teaching staff

Coordinator Salvatore Babones,
Lecturer(s) Salvatore Babones,
Type Description Weight Due Length
Assignment Final project
Replication study of findings from academic literature (continuous project)
30% Formal exam period
Due date: 05 Jun 2024 at 23:59
2000 words
Outcomes assessed: LO1 LO2 LO3 LO4
Assignment Assignment 1 (in lieu of exam)
Regression analysis of WVS data
35% Week 06
Due date: 27 Mar 2024 at 23:59
2000 words
Outcomes assessed: LO1 LO3 LO2
Assignment Assignment 2 (in lieu of exam)
Causal analysis of WVS data
35% Week 12
Due date: 15 May 2024 at 23:59
2000 words
Outcomes assessed: LO1 LO5 LO3 LO2

Assessment summary

Two papers have been set in lieu of exams, and the three homework assignments specified in the handbook entry have been combined in a final paper.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range


High distinction

85 - 100



75 - 84



65 - 74



50 - 64



0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

As per the Arts Handbook

Academic integrity

The Current Student website  provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.  

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy 2023 reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy 2023. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

WK Topic Learning activity Learning outcomes
Week 01 Introducing the World Values Survey Seminar (2 hr) LO1 LO2
Week 02 Means and medians; introduction to SPSS Seminar (2 hr) LO1 LO2 LO5
Week 03 Variance, Standard Deviation, and Z-scores Seminar (2 hr) LO1 LO3
Week 04 Simple linear regression: Correlation and R-squared Seminar (2 hr) LO1 LO2 LO3
Week 05 Simple linear regression: Expected and predicted values Seminar (2 hr) LO1 LO2 LO3 LO4
Week 06 Multiple linear regression Seminar (2 hr) LO1 LO2 LO3 LO4
Week 07 Statistical significance Seminar (2 hr) LO1 LO2 LO3 LO4
Week 08 ANOVA and mixed models Seminar (2 hr) LO1 LO2 LO3 LO4
Week 09 ANZAC DAY - no classes Seminar (2 hr)  
Week 10 Introduction to statistical programming Seminar (2 hr) LO1 LO5
Week 11 Interaction models Seminar (2 hr) LO1 LO3 LO4 LO5
Week 12 Logistic regression and introduction to limited dependent variable models Seminar (2 hr) LO1 LO3 LO4
Week 13 Additional limited dependent variable models Seminar (2 hr) LO1 LO3 LO4 LO5

Attendance and class requirements

  • Attendance: According to Faculty Board Resolutions, students in the Faculty of Arts and Social Sciences are expected to attend 90% of their classes. If you attend less than 50% of classes, regardless of the reasons, you may be referred to the Examiner’s Board. The Examiner’s Board will decide whether you should pass or fail the unit of study if your attendance falls below this threshold.

  • Lecture recording: Most lectures (in recording-equipped venues) will be recorded and may be made available to students on the LMS. However, you should not rely on lecture recording to substitute your classroom learning experience. IMPORTANT: This unit is taught as a hands-on seminar / workshop and thus only limited recorded lessons are available. Attendance in-person is absolutely essential.

  • Preparation: Students should commit to spend approximately three hours’ preparation time (reading, studying, homework, essays, etc.) for every hour of scheduled instruction.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

The supplemental textbook for this class, Social Statistics, is available free online at:

Necessary documentation for the class data are available online at:

Additional readings (both set and self-directed) will be assigned weekly throughout the semester.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. Obtain a general grounding in the basic principles of quantitative research in the social sciences.
  • LO2. Achieve competence in the graphical and tabular presentation of quantitative social science data.
  • LO3. Achieve competence in analyzing social science data using linear statistical models.
  • LO4. Achieve confidence in reading and evaluating statistical claims made in published social science results.
  • LO5. Become familiar with basic principles of statistical programming.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities

This section outlines changes made to this unit following staff and student reviews.

Unit content has been adjusted to account for the Anzac Day holiday.


The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.