- Class Number 4185
- Term Code 3130
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- AsPr Joanna Sikora
- Dr Bernard Baffour
- Dr Edith Gray
- Class Dates
- Class Start Date 22/02/2021
- Class End Date 28/05/2021
- Census Date 31/03/2021
- Last Date to Enrol 01/03/2021
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. Therefore, students will learn while designing and conducting their own research project, based on their investigation of survey data. The project will be written up as a research report that meets basic criteria set for survey-based publications in sociology, criminology or political science.
Upon successful completion, students will have the knowledge and skills to:
- understand and evaluate quantitative research articles;
- design a basic survey questionnaire and analyse survey data to answer specific research questions with cross-tabulations, t-tests, correlations and ordinary least squares regressions;
- understand the concept of random sampling and its relationship to statistical inferences;
- write survey analysis reports to professional standards; and
- formulate and answer ad hoc verbal queries about statistical procedures and software.
Students in this course are required to complete, under the guidance of instructors, an independently designed research project based on survey data. Students will choose one of the provided large, population-representative survey data sets. Then, they will propose a research project on which they will receive feedback and guidance on its further development. As the next step, students will complete data analyses for their project and write a report.
Additional Course Costs
It is recommended that students purchase a 6-month licence for Stata 16, Flavour Stata/IC available from https://www.stata-au.com/academics
However, students can access Stata software in all Information Commons areas on campus or via the Virtual Information Commons which involves no additional costs.
Examination Material or equipment
In case the exam is online: a reliable internet connection plus a working webcam to be used with the university Zoom account.
In case the exam is on-campus: a pen, a pencil and a non-programmable calculator.
To participate, students will need a personal computer with Microsoft Office and access to Stata 15 or 16. Students can access Stata via ANU Virtual Information Commons or on campus in Information Commons locations or through the purchase their own student Stata licence. Students will need an operational webcam and a reliable Internet connection to partake in classes, the exam, it is offered online, and stream course videos and use the Wattle site daily. I recommend that students 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).
The required readings for this course have been written by the course convenor and are in Wattle.
This course is supported with a selection of readings available in Wattle to extend and consolidate students’ knowledge. Moreover, students might find it useful to have some Stata data analysis manual and some book on survey research on hand to read them regularly. The books below are recommended, but students can use any book they like.
1. De Vaus, David 2013. “Surveys in Social Research.” London: Allen and Unwin, 6th Edition,
E-book available through the library website http://library.anu.edu.au/record=b3628743
2. Pevalin, David and Karen Robson. 2009. “The Stata Survival Manual.” Maidenhead: Open University Press, McGraw-Hill. E-book available through the library website http://site.ebrary.com/lib/anuau/detail.action?docID=10350202
It is recommended that students purchase a student licence of Stata if they envisage any difficulties in using the Virtual Information Commons or coming to campus.
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.
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). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.
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 need 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 get automatic extensions, even when their EAPs explicitly mention 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 other 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 homework, 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 their assignment files 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.
The preferred referencing style for this course is the American Psychological Association (APA) referencing style. Instructors recommend students use software called Endnote to format their references. Any style like the APA 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 will also need to complete before class. In class, instructors will go over these activities to help with any difficulties and answer any questions.
2. Students will allow sufficient time to prepare for classes and to revise after classes. The course has a strictly cumulative structure. To understand later material, students need to master earlier material.
3. Macs are not recommended for this course. Many students use them, and there have been no problems with Stata. Still, the instructors cannot assist with any difficulties related to PC/Mac compatibility as they have no access to Macs and do not test course materials on Macs. One issue instructors are aware of is that Macs do not correctly display images in the Word documents used as readings for this course. If students end up using Macs, they need to resolve any potential difficulties by talking to other students, saving Word documents as pdfs on a PC before transferring them to their Mac etc.
4. Due to COVID restrictions, instructors can accommodate up to 42 students in on-campus tutorials and labs. Other students will join online groups. If students sign up to an on-campus group, they will not be able, except when unwell and in possession of a medical certificate, to make online submissions to earn their lab/tutorial participation credit. On-campus students will not make weekly online submissions to earn participation credit. Off-campus students will have to make submissions, as per Wattle instructions, within 24 hours of the live online class. Students need to commit to their chosen mode of participation (on-campus or off-campus) at the beginning of the semester. Tutorials and labs will take place interchangeably at the same time each week, so students need to join only one group. The workshops will take place in lecture times, so students do not need to sign up for workshops.
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 cannot help students who missed classes and did not work 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. 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. All email queries about Assignment 2 should be accompanied by a copy of a properly constructed do file which identifies the dataset.
Basic notation and formulas used in this course are in Wattle.
|Week/Session||Summary of Activities||Assessment|
|1||1 Course structure, goals and challenges. 2 What is analysis? Conceptualisation: From research questions to indicators of concepts.||Tutorial 1: How to write a quantitative research paper?|
|2||3 From the philosophy of research to practicum in constructing a survey questionnaire. 4 Workshop 1: Practicum in questionnaire design.||Tutorial 2: Stata lab: Data entry and frequencies Assessment: Question Forum 1 opens|
|3||5 Descriptive statistics: typicality and variation (pre-recorded) 6 Data for quantitative research and levels of measurement||Tutorial 3: Stata lab: More on frequencies. Descriptives. Transforming variables. Assessment: Quiz 1|
|4||7 Probability and sampling 8 The normal distribution & z-scores||Tutorial 4: Random sampling and the Central Limit Theorem Assessment: Question Forum 2 opens|
|5||9 Using normal tables and validity and reliability in measurement 10 Crosstabulations and chi-square statistics||Tutorial 5: Stata lab: Transforming variables Assessment: Assignment 1|
|6||11 Workshop 2. Crosstabulations and computing chi-square statistics for crosstabulations 12 How to use crosstabulations in reports and publications||Tutorial 6. Stata lab: How to generate crosstabs and report chi-square tests. Assessment: Quiz 2|
|7||13 Hypotheses testing 14 Statistical inference in publications||Tutorial 7: Hypothesis tests: one-sided and two-sided tests for means and proportions Assessment: Quiz 3|
|8||15 Workshop 3: Practicum - statistical inference in publications||Tutorial 8: Stata lab: Hypotheses about means and proportions Assessment: Question Forum 3 opens|
|9||16 Correlations: conceptual underpinnings 17 Ordinary Least Squares Regression: foundations||Tutorial 9: Stata lab: How to produce correlations Assessment: Quiz 4|
|10||18 Ordinary Least Squares Regression: modelling assumptions 19 Multivariate Ordinary Least Squares Regression: conceptual issues||Tutorial 10: How to report correlations and regressions Assessment: Question Forum 4 opens|
|11||20 Workshop 4: Multivariate Ordinary Least Squares regressions in publications 21 Ethical considerations in quantitative research||Tutorial 11: Stata lab: How to create Ordinary Least Squares (OLS) regressions Assessment: Quiz 5|
|12||22 Predicted values in OLS + What to expect on the exam||Tutorial 12: Stata lab: How to apply predicted values from OLS models to answer research questions|
Each student must enroll into one Tutorial group. Tutorial registration will be available in Wattle.
|Assessment task||Value||Due Date||Return of assessment||Learning Outcomes|
|Data analysis proposal||10 %||25/03/2021||12/04/2021||1, 2, 3, 4|
|Data analysis report (based on cross-tabulations or other methods taught in SOCY2038)||35 %||20/05/2021||07/06/2021||1, 2, 3, 4|
|Formal exam||30 %||*||*||2, 3, 4|
|Five quizzes (worth 2% each)||10 %||*||*||1, 2, 3, 4|
|Participation||15 %||*||*||1, 3, 5|
* 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 Misconduct Rule before the commencement of their course. Other key policies and guidelines include:
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 ANU Online 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.
To pass the course, students must submit their data analysis proposal (Assignment 1), data analysis report (Assignment 2), sit the exam and meet the minimum participation requirements. Students must complete a minimum of nine required participation activities to pass. Students who do not participate in any on-campus or live online classes cannot meet Learning Outcome 5. Thus they cannot pass the course.
This course involves a formal final exam. Students are assessed on and receive credit for demonstrating the skills taught in this course.
Assessment Task 1
Learning Outcomes: 1, 2, 3, 4
Data analysis proposal
Assignment 1: Analysis proposal
Details: A separate document with Assignment 1 guidelines and assessment criteria will be available in Wattle. Please note that all guidelines are provided on the assumption that students know the course syllabus and the relevant lectures, tutorial and lab notes. Assignment 1 requires no references.
Word limit: 800 with 10% leeway
Credit value: 10%
Submission requirements: 1) In Wattle Assignment 1 Data Analysis by 11.55 pm
Estimated return date: Approximately two weeks for submissions received on time (when staff-to-student ratio does not exceed 1:40)
Feedback: Assessment rubric sheets (highlighted boxes) will be uploaded to Wattle. Additional written feedback will be uploaded to Wattle.
Research question and fit with chosen data
No clear research question or serious problems with the choice of variables/data; the assignment does not follow the guidelines
Neither the research question nor the chosen variables are optimal but the intentions of the author can be inferred
Either the research question all the variables chosen need minor adjustments; the research questions appropriate
Interesting research question; clearly stated and well motivated; good faith with the chosen variables
Original research question which is very clearly stated and strongly motivated; fits the chosen variables extremely well
Conceptual diagram with Stata variable names
No diagram or incorrect diagram
The diagram does not fully represent the logic of analysis
Good presentation of the diagram: some adjustment needed
Very good presentation of the diagram: mostly accurate and clear
Excellent presentation of the diagram: accurate and clear
Tables of descriptive statistics
No table of descriptors or incorrect data in the table
Table presentation needs major adjustments: levels of measurement; labelling; missing data; or decimal rounding
Table presentation needs minor adjustments: labelling missing data or decimal rounding
Table presentation shows good grasp of all concepts discussed in the course, including levels of measurement
Table presentation shows mastery of all concepts discussed in the course
Logical description of dependent and independent variables. Logical hypotheses
Now description of variable measurement, missing survey item wording. Hypotheses not listed or illogical.
Insufficient description of variable measurement, including, survey item wording without redundant elements. Hypotheses need major adjustments.
Good description of variable measurement, including survey item wording without redundant elements. Hypotheses need minor adjustments.
Very good description of variable measurement, including, survey item wording without redundant elements. Mostly logical and complete hypotheses.
Thorough description of variable measurement, including, survey item wording without redundant elements. Thorough and logical hypotheses.
Presentation: title, expression, structure, grammar, punctuation, pagination
For adherence to scholarly conventions
Written with limited adherence to scholarly conventions
Written according to scholarly conventions, but needs improvement in terms of expression and structure
Clearly written according to scholarly conventions
Very well written according to scholarly conventions
Assessment Task 2
Learning Outcomes: 1, 2, 3, 4
Data analysis report (based on cross-tabulations or other methods taught in SOCY2038)
Assignment 2: Analysis report (based on cross-tabulations or other methods taught in SOCY2038)
Details: A separate document with Assignment 2 guidelines and assessment criteria will be available in Wattle. Please note that all guidelines are provided on the assumption that students know the relevant course content.
Word limit (and other requirements): 2200 words with 10% leeway. Students will have to submit their Stata do-file (in a separate text or a .do file). The Stata do-files, references and appendices do not count towards the word limit. Everything else does.
Credit value: 35%
Submission requirements: 1) In Wattle Assignment 2 Data Analysis Report by 11.55 pm.
Note that the Stata do-file must be submitted as text (a pdf is not acceptable). The instructor must be able to copy the do-file into Stata and execute it. Non-executable do-files and papers based on materials and methods not taught in SOCY2038, will not receive credit.
Assignments submitted on time will be returned approximately two weeks later if the staff-to-students ratio does not exceed 1:40.
Feedback: Assessment rubric sheets (highlighted boxes) will be uploaded to Wattle. Additional oral feedback will be provided by appointment if requested.
Assessment Task 3
Learning Outcomes: 2, 3, 4
Formal examination. The details will be announced once the Examination Office releases the examination timetable. The exam will comprise multiple-choice questions, just as the ones in course quizzes and short problems of the type taught in workshops, labs and tutorials. In case students have to take the exam online, they will need a reliable Internet connection, a webcam and a backup connection (e.g., tethering a computer to a mobile phone as a Wi-Fi Hotspot). The standard university examination policies apply.
Assessment Task 4
Learning Outcomes: 1, 2, 3, 4
Five quizzes (worth 2% each)
Wattle Quizzes. The details and the schedule of quizzes will be discussed in Lecture 1. Each quiz will be available for 7 days beginning at 8 am on Monday morning. Students who do not attempt quizzes when they are available will not be able to access them later to revise.
Submission: Quizzes are in Wattle.
Assessment Task 5
Learning Outcomes: 1, 3, 5
Participation activities comprise four workshops, 12 tutorials and 4 question forums in Wattle. Students can earn a maximum of 15% of participation credit. It will comprise 3 out of 4 workshops (1% each), 10 out of 12 tutorials (1% each) and 4 question forum uploads (0.5% each). Students are encouraged to participate in all workshops, tutorials and question forums, to ensure they acquire all skills taught in the course.
There will be two modes of earning participation credit:
1) On-campus students will complete activities in class – students must prepare for these classes as per weekly instructions in Wattle. It is the student responsibility to remember to sign the roll in class.
2) Off-campus students must prepare for online classes, complete activities either during online class time or in their own time and upload class activities as per weekly instructions available in Wattle. To earn participation credit students take part in online classes. Students must log into Zoom using their university account.
Academic integrity is a core part of the ANU culture as a community of scholars. At its heart, academic integrity is about behaving ethically, committing to honest and responsible scholarly practice and upholding these values with respect and fairness.
The ANU commits to assisting all members of our community to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to be familiar with the academic integrity principle and Academic Misconduct Rule, uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with.
The Academic Misconduct Rule is in place to promote academic integrity and manage academic misconduct. Very minor breaches of the academic integrity principle may result in a reduction of marks of up to 10% of the total marks available for the assessment. The ANU offers a number of online and in person services to assist students with their assignments, examinations, and other learning activities. Visit the Academic Skills website for more information about academic integrity, your responsibilities and for assistance with your assignments, writing skills and study.
Students should keep a copy of the assignment for their records. Assignments must be submitted through Wattle. Students will be advised in lectures on how to access their assignment feedback.
There is are not hardcopy submissions in this unit.
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.
Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.
Feedback will be made available in Wattle. Students will be notified in the lectures about the availability of feedback and how to access it.
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.
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 Diversity and inclusion 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 and Learning Centre supports you make your own decisions about how you learn and manage your workload.
- ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
- ANUSA supports and represents undergraduate and ANU College students
- PARSA supports and represents postgraduate and research students
1. Educational gender segregation, i.e. processes that enhance the concentration of men and women in different fields of study; with a special interest in science
2. Role of adolescent aspirations and expectations in adolescent and adult life outcomes
3. Influence of heritability, parental background and scholarly culture in shaping educational and occupational pathways of youth and adults.
Broad interests involve social stratification and mobility, comparative survey sociology, educational inequalities, gender segregation in education, segregation in science education and sociology of education
AsPr Joanna Sikora
Dr Bernard Baffour