Students

SOCI8015 – Doing Social Survey Research

2021 – Session 1, Fully online/virtual

Notice

As part of Phase 3 of our return to campus plan, most units will now run tutorials, seminars and other small group activities on campus, and most will keep an online version available to those students unable to return or those who choose to continue their studies online.

To check the availability of face-to-face and online activities for your unit, please go to timetable viewer. To check detailed information on unit assessments visit your unit's iLearn space or consult your unit convenor.

General Information

Download as PDF
Unit convenor and teaching staff Unit convenor and teaching staff Unit Convenor
Hangyoung Lee
hangyoung.lee@mq.edu.au
Contact via Contact via Email
Room C311, 25C Wally's Walk
By appointment
Credit points Credit points
10
Prerequisites Prerequisites
Admission to MPSP or MPASR or GradCertPASR or GradDipPASR
Corequisites Corequisites
Co-badged status Co-badged status
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 science research. The unit looks closely at how to administer social surveys, how to write good survey questions and the debates about the potentials and limits of this methodology in the social sciences. Social surveys are usually designed to enable the statistical analysis of survey data, so the second part of the unit is dedicated to introducing students to a range of statistical models including multiple regression model. In this unit, students will learn R language for analysing survey data.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: demonstrate an understanding of the link between quantitative research design, survey procedure and statistical analysis.
  • ULO2: demonstrate and understanding of quantitative social science research critically.
  • ULO3: analyse survey data using appropriate statistical models.
  • ULO4: carry out a statistical analysis using R language.
  • ULO5: interpret statistical outputs in plain language.
  • ULO6: conduct original research using quantitative research methods.

General Assessment Information

Academic Integrity

Academic Integrity is an intergral part of the core values and principles contained in the Macquarie University Ethics Statement. Its fundamental principle is that all staff and students act with integrity in the creation, development, application and use of ideas and information. This means that:

  • All academic work claimed as original is the work of the author making the claim
  • All academic collaborations are acknowledged
  • Academic work is not falsified in any way
  • When the ideas of others are used, these ideas are acknowledged appropriately
  • Self-plagiarism (resubmitting your own work - including past assignments for this or other units - without attribution) is an unacceptable academic activity

More information is available from Policy Central here.

 

University Grading Policy

The grade that a student receives will signify their overall performance in meeting the learning outcomes of the unit of study. Graded units will use the following grades

HD    High Distinction    85-100

D       Distinction            75-84

Cr      Credit                   65-74

P        Pass                    50-64

F        Fail                       0-49

 

Return of Marked Work

As per university policy, written assessments will be returned to students within three weeks of the submission date. Early assignments will not be marked early.

 

Special Consideration (Extensions)

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:

  1. were serious, unexpected and unavoidable
  2. were beyond your control
  3. caused substantial disruption to your academic work
  4. substantially interfered with your otherwise satisfactory fulfilment of the unit requirements
  5. lasted at least three consecutive days or a total of 5 days within the teaching period and prevented completion of an assessment task scheduled for a specific date.

More information about Special Consideration is available here.

 

Late Penalties

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.

 

Campus Wellbeing

Macquarie University offers a range of wellbeing services (including [but not limited to]: health, welfare, counselling, disability and student advocacy services) that are available to you at any time during your studies. Campus Wellbeing is here to support you and help you succeed, both academically and personally. More information is available here.

Assessment Tasks

Name Weighting Hurdle Due
Quiz 20% No 29/03/2021
R analysis tasks 30% No Week 8, 10, 12 and 14
Survey research report 40% No 16/06/2021
Active participation 10% No On-going

Quiz

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 5 hours
Due: 29/03/2021
Weighting: 20%

Online quiz in week 6
On successful completion you will be able to:
  • demonstrate an understanding of the link between quantitative research design, survey procedure and statistical analysis.
  • demonstrate and understanding of quantitative social science research critically.

R analysis tasks

Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 16 hours
Due: Week 8, 10, 12 and 14
Weighting: 30%

Data analysis reports in week 7, 9, 11 and 13
On successful completion you will be able to:
  • analyse survey data using appropriate statistical models.
  • carry out a statistical analysis using R language.
  • interpret statistical outputs in plain language.

Survey research report

Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 40 hours
Due: 16/06/2021
Weighting: 40%

2,000 to 3,000 word research report
On successful completion you will be able to:
  • demonstrate an understanding of the link between quantitative research design, survey procedure and statistical analysis.
  • analyse survey data using appropriate statistical models.
  • carry out a statistical analysis using R language.
  • interpret statistical outputs in plain language.
  • conduct original research using quantitative research methods.

Active participation

Assessment Type 1: Participatory task
Indicative Time on Task 2: 10 hours
Due: On-going
Weighting: 10%

Active participation in unit sessions
On successful completion you will be able to:
  • demonstrate an understanding of the link between quantitative research design, survey procedure and statistical analysis.
  • demonstrate and understanding of quantitative social science research critically.
  • carry out a statistical analysis using R language.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

Seminar times

Seminars will take place on Mondays from 6 pm to 9 pm in 12 Second Way - 310 Tutorial Room. Seminar recordings and visual materials can also be accessed using ECHO360 on the iLearn.

 

Textbooks

This course draws on two required textbooks.

These textbooks can be accessed via Leganto on the iLearn.

 

Online Learning Platform

methods101.com is an online learning platform of quantitative research methods managed by Dr Hang Young Lee and Dr Nicholas Harrigan (Senior Lecturer of Sociology at MQ). This website provides online resources to help students learn statistical software programs. 

 

Technology used

The following technologies are used in the course:

iLearn

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.

 

AppStream

AppStream is the university's a new application streaming service which provides students access to existing iLab applications via browser from anywhere, anytime, on any device. Students do not need to install a client on their device to access applications. Google Chrome is recommended browser for AppStream. Login to mq.okta.com with your MQ OneID to access AppStream applications.

 

Turnitin and GradeMark

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.

 

R/RStudio

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:

R and RStudio are available in AppStream as well (see above). Week 2 seminar 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

Unit Schedule

Week

Class Topics

R Topics

1

Introduction to Survey Research Methods

No topic

2

Research Design

Introducing R and RStudio

3

Unit of Analysis and Empirical Measures

Creating Datasets

4

Ethics of Survey Research and Sampling Method

Playing with Variables

5

Survey Questionnaires and Survey Administration

No topic

6

Descriptive Statistics

Recoding Variables

7

Measures of Variability and Normal Distribution (1)

Univariate Statistics (1)

8

Normal Distribution (2) and Sampling Distribution

Univariate Statistics (2)

9

Confidence Intervals

Normal Distribution and Confidence Intervals

10

Hypothesis Test

Hypothesis Test (T-test)

11

Bivariate Table and Chi-sqaure

Crosstab & Chi-sqaure Test

12

Correlation and Simple Regression

Correlation and Simple Regression

13

Multiple Regression

Multiple Regression

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) 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 or if you are a Global MBA student contact globalmba.support@mq.edu.au

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

Learning Skills

Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to help you improve your marks and take control of your study.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Services and Support

Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.

Student Enquiries

For all student enquiries, visit Student Connect at ask.mq.edu.au

If you are a Global MBA student contact globalmba.support@mq.edu.au

IT Help

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.

Unit information based on version 2021.02 of the Handbook