In the 21st century sociologists, criminologists and political scientists can access a wealth of data contained in 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 practices of exploratory data analysis. Second, they will learn about the basics of statistical data analysis and how understand how to use data samples to test claims about social groups and their differences. Finally, they will develop skills in critical data analysis allowing them to situate statistical practice in the context of contemporary social processes, knowledges and power relations.

The course is based on a problem-based pedagogy. Students will work with 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, chi-squared tests and estimates with confidence intervals.

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 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.

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

Online resources will be linked from the Canvas site.

Recommended Resources

Whether you are on campus or studying online, there are a variety of online platforms you will use to participate in your study program. These could include videos for lectures and other instruction, two-way video conferencing for interactive learning, email and other messaging tools for communication, interactive web apps for formative and collaborative activities, print and/or photo/scan for handwritten work and drawings, and home-based assessment.

ANU outlines recommended student system requirements to ensure you are able to participate fully in your learning. Other information is also available about the various Learning Platforms you may use.

Staff Feedback

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

• written comments
• verbal comments
• feedback to whole class, groups, individuals, focus group etc

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.

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	Whose data?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 categoriesThis 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.
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	What is happening to quantitative data now in the early 21st century? The rise of data science and machine learning has re-shaped practices of working with data, especially to address the many forms of data generated on digital platforms (links, tags, comments, etc.). But this was preceded by the emergence of non-statistical forms of quantitative data analysis focused on patterns and clusters. AI-supported data analysis is also increasingly available.	Work on the research project continues. And the final piece of classical statistical data analysis is introduced: the chi-squared test for relationships between categorical variables.
11	Group research project presentations	This week is given over to project presentations and feedback on them. Everyone will be involved in giving structured feedback to each other.
12	The workshop this is focused on reviewing the main approaches to quantitative methods in the course, as well as planning the final report. We will carry out some practical experiments in structuring and organising the final report.	Preparation for submission of final report

Tutorial Registration

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

Assessment Summary

Assessment task	Value	Learning Outcomes
Learning Log	25 %	1
Online quizz	10 %	1,2,3,4
Online quiz	10 %	1,2,3,4
Group presentation	15 %	2,3,5
Research project report	40 %	5

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

Policies

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:

• Academic Integrity Policy and Procedure
• Student Assessment (Coursework) Policy and Procedure
• Extenuating Circumstances Application
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure
• Code of practice for teaching and learning

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 ‘Canvas’ 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

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.

Examination(s)

There is no examination for the course

Assessment Task 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

Assessment Task 2

Online quizz

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

Assessment Task 3

Online quiz

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

Assessment Task 4

Group presentation

Group presentation and report on participation 15% week 11

Assessment Task 5

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

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Individual assessment tasks may or may not allow for late submission. Policy regarding late submission is detailed below:

• Late submission not permitted. If submission of assessment tasks without an extension after the due date is not permitted, a mark of 0 will be awarded.
• Late submission permitted. Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

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. Any use of artificial intelligence must be properly referenced. Failure to properly cite use of Generative AI will be considered a breach of academic integrity.

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.

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).

• ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
• ANU Accessibility for students with a disability or ongoing or chronic illness
• ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
• ANU Academic Skills supports you make your own decisions about how you learn and manage your workload.
• ANU Counselling promotes, supports and enhances mental health and wellbeing within the University student community.
• ANUSA supports and represents all ANU students