Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor
Hangyoung Lee
Contact via Email
South Wing on Level 2, Australian Hearing Hu
By appointment
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Prerequisites |
Prerequisites
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Corequisites |
Corequisites
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Co-badged status |
Co-badged status
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Unit description |
Unit description
This is a unit in applied survey research and data analysis. It will explain key survey techniques used and give you the chance to try them out in practice. The unit covers choosing survey methods, administering surveys and writing good survey questions. It also looks at some of the debates around the potentials and limits of surveys. Qualitative researchers often rely on surveys to prepare themselves for fieldwork or to 'triangulate' their results from interview work. But ultimately, surveys are designed to enable statistical analysis of data, and therefore the unit covers some of the statistical techniques used. Understanding how quantitative analytical methods work with and augment qualitative methods requires some knowledge and use of statistics and a statistical package.
All enrolment queries should be directed to Open Universities Australia (OUA): see www.open.edu.au
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Information about important academic dates including deadlines for withdrawing from units are available at https://www.open.edu.au/student-admin-and-support/key-dates/
On successful completion of this unit, you will be able to:
Name | Weighting | Hurdle | Due |
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Online Quiz | 30% | No | 5th September |
Analysis Tasks | 30% | No | Week 7, 8, 9, 11 and 12 |
Survey Research Report | 30% | No | 11th November |
Course Participation | 10% | No | Ongoing |
Due: 5th September
Weighting: 30%
Online quiz will consist of 40 multiple-choice or true-or-false questions, and you will have 60 minutes to complete it. You will be asked to read each question and select the BEST response from the available options. This quiz will draw on course materials from the lectures and workshops from week 1 to week 5.
The online quiz will become available on Monday 3rd September, and you can undertake the quiz until Wednesday 5th September (at 11:59 pm EST). It will become available via the course iLearn page. The quiz can be taken only once, and it is up to you to ensure that you have time available to undertake the quiz.
More information will become available in week 4 and 5 of the semester. Please follow the Special Consideration policy when applying for an extension. As per the Faculty of Arts policy, no late submissions will be accepted for the online quiz without an extension.
Note) In the event of technical difficulties, it is your responsibility to contact the unit convenor before the due date and follow the instructions on iLearn in notifying the university. We advise you to ensure that you can access the link to the quiz on Monday 3rd September (without starting the quiz unless you want to).
Due: Week 7, 8, 9, 11 and 12
Weighting: 30%
Students will have five analysis tasks, which are take-home assignments. In week 7, 8, 9, 11 and 12, students will be required to complete and submit each analysis task in due time after the class. These tasks are intended to assess students’ skills to analyse survey datasets using R. They consist of several statistical problems that students should address. Each task contributes to 6% of students’ overall assessment. Using R is a must for this task. Students will learn all the necessary R coding in the classes from week 6 to week 12.
Each task will be posted on the iLearn page. The report should be submitted via Turnitin, and it will be marked via GradeMark. Please do not submit hard copies of this task and ensure that you have access to the Turnitin link before the due date. More information will be provided on iLearn.
Due: 11th November
Weighting: 30%
This task is a research paper of 2,000 to 3,000 words. This task is designed to assess students’ overall ability to address social science inquiries using quantitative research skills. It will require you to select a research topic, formulate research hypotheses, analyse the related dataset, and interpret the statistical outcomes. Using R is a must for this task.
For the data analysis, three Australian datasets will be provided on the iLearn page: the 2009 Australian Survey of Social Attitudes (which focuses on social inequality), the 2012 Australian Survey of Social Attitudes (which focuses on family and gender) and Crime Rates Datasets for NSW Local Government Areas. Students will be free to choose one of these datasets or other datasets that fit for their research projects. The report should be submitted via Turnitin, and it will be marked via GradeMark. Please do not submit hard copies of this task and ensure that you have access to the Turnitin link before the due date. More information will be provided in week 8 of the semester.
Due: Ongoing
Weighting: 10%
OUA students are required to listen to the lectures online and download class resources on a weekly basis. OUA students’ course participation will be assessed based on their online activities on the iLearn (e.g., visiting the iLearn page, listening to online lectures, downloading class resources or engaging in online discussion). Please use the board of “General discussion” on the iLearn to discuss class topics and share related materials you have found outside of class. Those who engage actively in the General discussion board (e.g., those who raise a question, reply to a question, lead a discussion about assigned readings and class topics, or share useful external resources) will get high scores for course participation.
Lectures will take place on Thursdays from 6 pm to 8 pm (and longer if needed) in 4 Western Rd - 232 Tutorial Rm (previously W5C 232). Lecture recordings and visual materials can also be accessed using ECHO360 on the iLearn.
This course draws on two required textbook.
Vaus, David de (2014) Surveys in Social Research, 6th Edition, Allen&Unwin.
Illowsky, Barbara and Susan Dean (2017) Introductory Statistics, OpenStax. (Available for free at https://openstax.org/details/books/introductory-statistics )
It is recommended to read the following textbook if students seek for more comprehensive understanding of R.
Verzani, John (2014) Using R for Introductory Statistics, 2nd Edition, Taylor&Francis
The following technologies are used in the course:
Important information about the weekly schedule for the course, course readings and assessment are all available on the course iLearn page. If you do not have access, please contact IT help. You are required to check iLearn and your student email regularly for course updates and information.
iLab is the university's Remote Desktop system that allows you to connect to university computers remotely. It allows you to use R over the internet on- and off-campus computer (desktop computer or laptop). If students cannot access iLab, the university has some computers with R in the library and digital lounge (C5C - 17 Wally’s Walk) that are available to students outside of class hours. Please note that these labs can become very busy during peak periods.
The written assessment for the course needs to be submitted via Turnitin. A link to Turnitin is available via the Assessments tab on the iLearn page. Please contact the convenor if you cannot find it (do not leave it until the due date of the assessment). Assessments will be marked via GradeMark and returned to students electronically.
Qualtrics is an online survey platform that makes it easy to build a survey and to collect survey data. Students can access Qualtrics using Macquarie University OneID and password at https://mqedu.qualtrics.com.
R is the name of the statistical programming language, and RStudio is a convenient interface of R. You can download both R and RStudio for free at:
RStudio: https://www.rstudio.com
R and RStudio are available in iLab as well (see above). Week 6 class will introduce how to install R and RStudio. After setting up R and RStudio, it is also necessary to install the following packages for the course:
summarytools
sjPlot
sjmisc
sjlabelled
tidyverse
gmodels
gplots
Week 1: Introduction to Social Survey Research
Week 2: Quantitative Research Design
Week 3: Unit of Analysis, Measurements and Sampling
Week 4: Sampling Method and Constructing Survey Questionnaires
Week 5: Survey Administration
Week 6: Introduction to R and RStudio
Week 7: Univariate Analysis
Week 8: Normal Distribution and Sampling Distribution
Week 9: Estimating Confidence Intervals
Week 10: Testing Hypotheses
Week 11: Bivariate Association
Week 12: Regression Analysis
Week 13: Multiple Regression Analysis
Unless a Special Consideration request has been submitted and approved, (a) a penalty for lateness will apply – two (2) marks out of 100 will be deducted per day for assignments submitted after the due date – and (b) no assignment will be accepted more than seven (7) days (incl. weekends) after the original submission deadline. No late submissions will be accepted for timed assessments – e.g. quizzes, online tests.
The University recognises that students may experience events or conditions that adversely affect their academic performance. If you experience serious and unavoidable difficulties at exam time or when assessment tasks are due, you can consider applying for Special Consideration.
You need to show that the circumstances:
If you feel that your studies have been impacted submit an application as follows:
Outcome
Once your submission is assessed, an appropriate outcome will be organised.
You can withdraw from your subjects prior to the census date (last day to withdraw). If you successfully withdraw before the census date, you won’t need to apply for Special Circumstances. If you find yourself unable to withdraw from your subjects before the census date - you might be able to apply for Special Circumstances. If you’re eligible, we can refund your fees and overturn your fail grade.
If you’re studying Single Subjects using FEE-HELP or paying up front, you can apply online.
If you’re studying a degree using HECS-HELP, you’ll need to apply directly to Macquarie University.
Macquarie University policies and procedures are accessible from Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central). Students should be aware of the following policies in particular with regard to Learning and Teaching:
Undergraduate students seeking more policy resources can visit the Student Policy Gateway (https://students.mq.edu.au/support/study/student-policy-gateway). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.
If you would like to see all the policies relevant to Learning and Teaching visit Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central).
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/study/getting-started/student-conduct
Results shown in iLearn, or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au.
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.
Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.
For all student enquiries, visit Student Connect at ask.mq.edu.au
For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/.
When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.
Our postgraduates will demonstrate a high standard of discernment and common sense in their professional and personal judgment. They will have the ability to make informed choices and decisions that reflect both the nature of their professional work and their personal perspectives.
This graduate capability is supported by:
Our postgraduates will be able to demonstrate a significantly enhanced depth and breadth of knowledge, scholarly understanding, and specific subject content knowledge in their chosen fields.
This graduate capability is supported by:
Our postgraduates will be capable of utilising and reflecting on prior knowledge and experience, of applying higher level critical thinking skills, and of integrating and synthesising learning and knowledge from a range of sources and environments. A characteristic of this form of thinking is the generation of new, professionally oriented knowledge through personal or group-based critique of practice and theory.
This graduate capability is supported by:
Our postgraduates will be capable of systematic enquiry; able to use research skills to create new knowledge that can be applied to real world issues, or contribute to a field of study or practice to enhance society. They will be capable of creative questioning, problem finding and problem solving.
This graduate capability is supported by:
Our postgraduates will be able to communicate effectively and convey their views to different social, cultural, and professional audiences. They will be able to use a variety of technologically supported media to communicate with empathy using a range of written, spoken or visual formats.
This graduate capability is supported by:
Our postgraduates will be ethically aware and capable of confident transformative action in relation to their professional responsibilities and the wider community. They will have a sense of connectedness with others and country and have a sense of mutual obligation. They will be able to appreciate the impact of their professional roles for social justice and inclusion related to national and global issues
This graduate capability is supported by:
Date | Description |
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17/07/2018 | The classroom has been changed. |