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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Credit points |
Credit points
4
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Prerequisites |
Prerequisites
Admission to MPASR or GradCertPASR or GradDipPASR or MIntPubDip or MPASRMDevStud or MSecStrategicStud or MIntell or MCTerrorism or MCyberSec or GradDipSIA or GradCertSIA
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Corequisites |
Corequisites
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Co-badged status |
Co-badged status
SOCI702
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Unit description |
Unit description
Social surveys are now used widely in policymaking, public debate, and social research. This unit provides students with a practical and theoretical guide to the use of surveys in social research. We look closely at how to administer social surveys, how to write good survey questions, and some of the debates about the potentials and limits of this methodology in the social sciences. Social surveys are usually designed to enable statistical analysis of survey data, so the second part of the unit is dedicated to introducing students to a range of data techniques including multivariate analysis. Students will use R in data analysis.
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Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-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%
Students are expected to attend weekly lectures. To meet the requirements of this course, you need to attend at least 80% of the lectures (not counting excused absences). Also, you are expected to participate actively. Students who score highly for course participation will be those who arrive to class on time, actively discuss assigned readings, share related materials they have discovered outside of class, and make connections to additional topics that enhance our course. Attendance is tremendously important. Missing classes will diminish this part of your grade. If a student is absent from more than three lectures, he or she will lose all course participation points.
If you are unable to attend the lecture, you can meet your lecture participation requirement by submitting 300 to 400 word summaries of the lectures via the iLearn page.
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
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.
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Date | Description |
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17/07/2018 | The classroom is changed. |