• Class Number 4115
  • Term Code 3430
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Prof Adrian Mackenzie
  • Class Dates
  • Class Start Date 19/02/2024
  • Class End Date 24/05/2024
  • Census Date 05/04/2024
  • Last Date to Enrol 26/02/2024
SELT Survey Results

In the 21st century sociologists, criminologists and political scientists can access a wealth of information contained in survey data repositories. To enable students to evaluate the quantitative literature and analyse survey data themselves, this course lays the foundations for three types of skills.

First, students will consider the theoretical underpinnings of survey design. Second, they will learn about the basics of statistical theory and understand which samples do and do not represent populations of interest. Finally, they will learn to use Stata, a software package that many social scientists choose for data analysis. 

The course is based on an inquiry-led pedagogy. Students will interrogate survey data to learn how to produce and interpret descriptive and inferential statistics. Course activities will enable students to learn how to ask and answer research questions using techniques that include cross-tabulations, t-tests, correlations and ordinary least squares regressions.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1.  critically evaluate key quantitative methodologies using historical, critical and ethical approaches including indigenous perspectives;
  2.  interpret and analyse sociological or social science research that uses statistical methods;
  3.  use quantitative and statistical techniques to analyse social issues; and
  4.  define key statistical concepts and explain how they can be used in social science .

Research-Led Teaching

This course is oriented to some of the major transformations in methods for working with quantitative data over the last few decades. It is informed recent debates in critical data studies, changes in research practice associated with proliferation of software for working with data, visualising it and modelling.

Required Resources

To participate, students will need to bring a laptop computer. Students might need an operational webcam and a reliable Internet connection to partake in online classes, if such classes are offered, to stream course videos and use the Wattle site. Students should organise a backup connection (e.g. learn how to tether their computer to their mobile phone and use the latter as a Wi-Fi hotspot).

 All required readings for this course have been written by the course convenor and are in Wattle. All recommended readings are also listed in Wattle.

This course is supported by a selection of readings available in Wattle to extend and consolidate students’ knowledge.


Staff Feedback

Students will be given feedback in the following forms in this course:

  • Written comments on Assignment 1 unless submission is late.
  • Verbal comments on Assignment 2 by appointment.
  • Oral feedback to the whole class during lectures, tutorials and PC labs.

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Other Information

Students with Educational Access Plans

Students who have been issued with an Educational Access Plan by Access and Inclusion Services, are requested to email a copy to the course convener and their tutor as soon as they receive it. In all relevant communication, students are asked to remind their instructors about their EAP. Please include a copy of the EAP in each request for an extension made via Wattle. Students with EAPs do not have extensions by default on all their quizzes or assignments, even when their EAP explicitly mentions quizzes. It is best to make a time to discuss each EAP to avoid misunderstandings.

Missed class policy

Students who have a medical certificate to excuse their absence from a workshop, tutorial or lab, and wish to make up participation credit need to email their certificate to the course convenor along with evidence of completed tutorial or lab activities. Students whose circumstances prevent them from timely completion of course activities can apply for extensions, but these will be granted on a case-to-case basis.

Keeping track of marks and avoiding submission mishaps

Students will see their marks as they appear in their Wattle grade book. They are requested to check their record and notify the course convenor within two weeks about any errors. It is the students’ responsibility to retain a copy of their submitted work, which must be presented in any dispute with the instructors. This means that students must back up not only data analyses report but their data files and programming files (i.e. files with data analysis commands/do files/syntax files). Occasionally a submitted file is corrupt and cannot be opened. It is the students’ responsibility to carefully check that their submission opens correctly on a PC before submitting. 

Support for students

The University offers many support services for students. Information on these is available online from http://students.anu.edu.au/studentlife/


International and culturally diverse students

The University offers special assessment arrangements for Students from Language Backgrounds other than English. If students wish to utilise them, they need to follow the steps outlined in https://policies.anu.edu.au/ppl/document/ANUP_004603 The course convenor can answer questions about this policy but students must first read Sections 29 through 32. 

 The course convenor will be happy to see if students can be provided with a survey dataset that originates from a country other than Australia if students prefer to complete their Assignments 1 and 2 using such a dataset. This request must be made by Week 3.



Referencing requirements

The preferred referencing style for this course is the Harvard referencing style. Instructors recommend students use software such as Zotero or Endnote to format their references. Any style like the Harvard style is acceptable, but it must be used consistently. Only sources read in full ought to be used as references.

Mode of Work

1.    In this course, students must complete the required readings before class. Some readings include preparatory activities which students need to complete before class. In class, instructors will go over these activities to help with any difficulties and answer questions.

2.    Students will allow sufficient time to prepare for classes and to revise after classes. The course has a cumulative structure. To understand later material, students need to master earlier material.

3.    Laptops will be used in all classes. As a practice-based course, use of a laptop during classtime is a basic requirement.



Instructors will be happy to offer individual consultations to discuss, clarify or expand on any issues in the course organisation, delivery or material. However, instructors usually cannot help students who missed classes and have not worked through the class materials before asking for a consultation. Instructors cannot give students any real help a couple of days before an assignment is due, so please schedule a meeting at least a week in advance of the assignment due date. Instructors will not provide comments on assignment drafts and are usually unable to deal with Stata programming problems unless they can see what students are doing on their screen or receive their complete do file. Following the return of Assignment 1 all email queries about Assignment 2 should have in an attachment a copy of the full assignment do file which identifies the dataset. 

 Basic notation and formulas used in this course are in Wattle in a pdf version of this class summary.

Class Schedule

Week/Session Summary of Activities Assessment
1 Introduction and organisation of the course Workshop on getting devices set up for the course, and setting up for 'Introduction to Statistics' online materials.
2 Observing, describing and abstractingExploring quantities and social research with quantities, with the aim of getting a sense of some of the very different practices found in recent research. Introduce the idea of the social life of methods. Workshop will include gathering and exploring some quantitative data in Excel and R
3 DescriptionsApproaches to describing quantities using statistics, and an introduction to critical analyses of statistical practice. Practical work on generating descriptions of sets of numbers and other forms of data; Online quiz 1
4 What is normal?Perhaps the most outstanding feature in many quantitative research methods is the calculation or estimation of the central tendency, or, what is *normal.* . We will explore the legacies of nineteenth century and early twentieth century statistical practice in the context of national census. Practice working using techniques to examine distributions of different types of data. These include measures of spread, and practices of normalization (such as z-scores).
5 The focus in this session is on the political/institutional significance of quantitative methods with specific reference to whose data and whose methods of numeracy count. We will discuss these in the context of indigenous data sovereignty and in critical social research into global development data and its intellectual and political compromises. Undertake initial exercises in comparing groups of people using numerical and categorical data. Experiment with ways of examining relationships between social groups visually.
6 Relations between groups
Social research is full of techniques and methods focused on the differences between groups. For instance, much research on inequality starts from the idea that inequality comes from differences between groups. How can differences between groups be known using quantitative methods? Many social researchers effectively count how many people fit within certain categories (e.g. class, income bracket, ethnicity, religion, gender, etc.).
Practical work for this week focuses on counting categories, and comparing categories.using cross-tabulations. Online quiz 2
7 Statistics as a testing practiceMuch quantitative social research methods for testing and estimating relationships in data. We focus on just two: techniques for inferring relationships between different groups given a measure or observation of some quantitative difference (e.g. income); techniques for inferring relationships between different categories (e.g. attitudes to social media and taste in music). Practical work for this week focuses on the t-test and how it can be used to make inferences about the means of different groups.Initial planning for group projects
8 Statistics for categories This week, we will compare groups in terms of categories. Much social research work with categories, and seeks to either describe those categories or examine the relation between different categories. For instance, Pierre Bourdieu's *Distinction: Social Critique of Taste* depends on examining how different categories of consumption (food, media, art, housing, etc.) vary in relation to each other. Practical work this week concerns how to statistically test the relations between different categories using the Chi-squared test.Learning log due
9 Modelling relationshipsGroup research projects start. These will have been discussed and mentioned quite a few times already in the course, but for the next three weeks, our time together will be organised around work on the research projects. The projects are intended to provide you with structured opportunity to try out skills in quantitative data analysis and critical thinking about data.

The session will be a mixture of practical work with the datasets described in the research project, and group planning for the project.
10 Approaching relationships with uncertainty

Tutorial 10:How to report correlations and regressions
11 Lecture 10 duration 1 hour:Predicted values in OLSWorkshop 4 duration 1 hour: Multivariate Ordinary Least Squares regressions in publications Tutorial 11:Stata lab: How to create Ordinary Least Squares (OLS) regressionsAssessment: Quiz 5
12 Lecture 11 duration 2 hour:Literature review, ethical considerations in quantitative research, the future research frontier and wrap up Tutorial 12:Stata lab: How to apply predicted values from OLS models to answer research questions, ethics in research

Assessment Summary

Assessment task Value Learning Outcomes
Assignment 1: Learning log 25 % 1
Assignment 2: Online quiz 10 % 1,2,3,4
Assignment 3: Online quiz 10 % 1,2,3,4
Group research project presentation 15 % 2,3,5
Research project report 40 %

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details


ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.


Participation in group projects is a core learning element of the course. Groups will have opportunities to reflect on styles of participation and students will reflect individually on their participation in group work.



This is not a formal exam for the course.

Assessment Task 1

Value: 25 %
Learning Outcomes: 1

Assignment 1: Learning log

A reflexive learning report such as a learning journal that will document process of learning exploratory data analysis, statistical tests and critical insights into methods throughout the course; 1500 words 25%; week 8

Assessment Task 2

Value: 10 %
Learning Outcomes: 1,2,3,4

Assignment 2: Online quiz

Online quizzes on basic concepts and techniques in quantitative data analysis; 10% week 3

Assessment Task 3

Value: 10 %
Learning Outcomes: 1,2,3,4

Assignment 3: Online quiz

Online quizzes on basic concepts and techniques in quantitative data analysis; 10% week 6

Assessment Task 4

Value: 15 %
Learning Outcomes: 2,3,5

Group research project presentation

Group presentation and report on participation 15% week 11

Assessment Task 5

Value: 40 %
Learning Outcomes: 

Research project report

A report documenting findings from a group research project focused on the analysis of a contemporary dataset using exploratory, critical and statistical testing approaches 40% week 13

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.


The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

Students should keep a copy of the assignment for their records. Assignments must be submitted through Wattle. Students will be advised in lectures or via the Wattle Course Noticeboard on how to access their assignment feedback.

Hardcopy Submission

There is are no hardcopy submissions in this unit.

Late Submission

The course convenor assumes that each student has one three-day extension either for Assignment 1 or 2. Students must apply for an extension via Wattle and they will be granted their first three-day extension without any documentation. This provision allows for dealing with unexpected circumstances such as a change in work schedule, brief illness, failure of the Internet connection etc. The extension will not be split. The second extension will only be given in case of severe adversities or health problems. Should they occur, documentation will be required. No retrospective extensions will be given. Problems with access to the Internet or Stata will generally not suffice as grounds for an extension, so students must ensure they have a backup Internet connection and a backup plan for accessing Stata if their usual mode of access fails.

For all late submissions, the ANU late submission policy (available at https://cass.anu.edu.au/current-students/coursework-policy-and-guidelines/late-submissions-and-extensions ) will apply. If your assignment is late, with or without an extension, your feedback will be late.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

Returning Assignments

Feedback will be available in Wattle. Students will be notified in the lectures or through the Wattle Course Noticeboard about the availability of feedback and how to access it.

Written work will receive individual written feedback. Individual and collective feedback will provided informally throughout the course.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments

Students will not normally be able to resubmit their assignments.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Prof Adrian Mackenzie

Research Interests

platforms, ecologies, habit, change

Prof Adrian Mackenzie

Friday 16:00 17:00
By Appointment

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions