Students

SSCI2020 – Survey Research in the Social Sciences

2024 – Session 2, Online-flexible

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Unit Convenor and Lecturer
Hangyoung Lee
Contact via Contact via Email
Room B270, Level 2 25B Wally's Walk
By appointment
Tutor
Luke Ashton
Contact via Contact via Email
By appointment
Credit points Credit points
10
Prerequisites Prerequisites
SSCI100 or SSCI1000 or SSC100
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

The unit introduces students to the logic of quantitative social inquiry, with a specific focus on social surveys. Social surveys are widely employed in today’s social science workplaces, with an array of uses in policy-making, public debate and social research. Survey methodologies collect systematic information about cases and present this information in a structured ‘data grid’, which can be used to test theoretically informed hypotheses and inferences. Surveys are used in many different types of studies, from quasi-experiments to cross-sectional and longitudinal studies. Building on SSCI1000 and SSCI2010, the unit focuses on linking quantitative research design to data analysis, including the deductive logic of quantitative research and analysis. Students learn how to develop survey questionnaires and collect other forms of quantitative data, as well as how to use computer software to analyse survey data. The unit aims to show that credible findings from survey research are as reliant on collecting valid and reliable data as they are on applying relevant analytic techniques.

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: Understand the link between quantitative research design, survey procedure and statistical analysis
  • ULO2: Analyse survey data using appropriate statistical models.
  • ULO3: Carry out a statistical analysis using SPSS.
  • ULO4: Interpret statistical outputs in plain language.
  • ULO5: 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

 

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

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.

 

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 in the Policies and Procedures section of the unit guide.

 

Late Penalties

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark) will be applied each day a written assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a mark of ‘0’ (zero) will be awarded even if the assessment is submitted. Submission time for all written assessments is set at 11.55 pm. A 1-hour grace period is provided to students who experience a technical issue. This late penalty will apply to non-timed sensitive assessment (incl essays, reports, posters, portfolios, journals, recordings etc). Late submission of time sensitive tasks (such as tests/exams, performance assessments/presentations, scheduled practical assessments/labs etc) will only be addressed by the unit convenor in a Special consideration application. Special Consideration outcome may result in a new question or topic.

 

Student 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 in the Policies and Procedures section of the unit guide.

Assessment Tasks

Name Weighting Hurdle Due
Quiz 1 20% No 2024-09-01
Quiz 2 20% No 2024-10-27
Data Analysis Report 40% No 2024-11-03
Active participation 20% No Ongoing

Quiz 1

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 4 hours
Due: 2024-09-01
Weighting: 20%

 

First Online Quiz

 


On successful completion you will be able to:
  • Understand the link between quantitative research design, survey procedure and statistical analysis
  • Analyse survey data using appropriate statistical models.
  • Interpret statistical outputs in plain language.

Quiz 2

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 4 hours
Due: 2024-10-27
Weighting: 20%

 

Second Online Quiz

 


On successful completion you will be able to:
  • Understand the link between quantitative research design, survey procedure and statistical analysis
  • Analyse survey data using appropriate statistical models.
  • Interpret statistical outputs in plain language.

Data Analysis Report

Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 42 hours
Due: 2024-11-03
Weighting: 40%

 

1,800 to 2,000 word research report

 


On successful completion you will be able to:
  • Understand the link between quantitative research design, survey procedure and statistical analysis
  • Analyse survey data using appropriate statistical models.
  • Carry out a statistical analysis using SPSS.
  • 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: 11 hours
Due: Ongoing
Weighting: 20%

 

Active participation in unit

 


On successful completion you will be able to:
  • Understand the link between quantitative research design, survey procedure and statistical analysis
  • Carry out a statistical analysis using SPSS.

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

Lecture and workshop times

Lectures will take place on Mondays from 1 pm to 3 pm in 14 Sir Christopher Ondaatje Ave - T4 Theatre. Lecture recordings and visual materials are available on the iLearn.

The Workshop instructions are available at https://methods101.com.au. Click SSCI2020 at the left sidebar. You will see 11 workshop guidelines. For completing Workshop tasks, students can seek help and advice from tutors via External forums in the course iLearn page and emails. Fully online students MUST follow the workshop instruction each week and participate in the workshop participation activity to get participation marks. The links to the workshop participation activity are available on the course iLearn page.

Textbooks

This course draws on one required textbook:

  • Leon-Guerrero, Anna and Chava Frankfort-Nachmias (2018) Essentials of Social Statistics for a Diverse Society, 3rd Edition. Sage: Thousand Oaks.

For those who find the required textbook difficult to read,  the following textbook(optional) is recommended:

  • Wheelan, Charles J. (2014) Naked Statistics: Stripping the Dread from the Data, W.W. Norton & Company.

Technology used

The following technologies are used in SSCI2020:

Email

Make sure that you regularly check your student email for correspondence with teaching staff and course announcements.

iLearn

Important information about the weekly schedule for SSCI2020, 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.

SPSS

SPSS is the primary statistical analytic tool for SSCI2020. Learning SPSS to analyse datasets is an essential component of this unit. SPSS is available in the workshops and some computers in the library and digital lounge (C5C - 17 Wally’s Walk). Students can also access remotely SPSS through AppStream (see below).

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.

Methods101.com.au

Workshop guidelines are available at https://methods101.com.au. The website provides easy-to-follow instructions on how to use SPSS to analyse data. In the website, click SSCI2020 at the left sidebar. Then, you can access the guidelines for each workshop. If you do not have access, please contact the unit convenor.

Turnitin and GradeMark

The written assessment for SSCI2020 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.

Leganto

Leganto is the electronic system for accessing unit readings that can be accessed via the iLearn page. Readings are allocated by weekly schedules. As well as the required readings for each week, you will find recommended and optional readings. The required readings are available in pdf or electronic format. If you are not able to access the readings, please contact the unit convenor via email.

Zoom

Zoom is an online video conferencing software platform. It is used for optional meetings and consultations.

Unit Schedule

Week Lecture SPSS Workshop
1 Introduction to Quantitative Research Methods No workshop
2 Quantitative Research Design Introduction to SPSS
3 Univariate Statistics Exploratory Data Analysis 1
4 Statistical Charts and Normal Distribution Exploratory Data Analysis 2
5 Normal Distribution Normal Distribution and Z-scores
6 Sampling and Sampling Distribution Random Sampling Experiment
7 Estimating Confidence Intervals Computing Confidence Intervals 
8 Testing Hypotheses T-test
9 Bivariate Association Cross-table and Chi-square
10 Correlation and Regression Correlation and Regression Analysis
11 Multiple Regression Model Multiple Regression Analysis 1
12 Dummy Variables in Regression Model Multiple Regression Analysis 2
13 Consultation for Data Analysis Report Consultation for Data Analysis Report

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 connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

Student Support

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

The Writing Centre

The Writing Centre provides resources to develop your English language proficiency, academic writing, and communication skills.

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

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via the Service Connect Portal, or contact Service Connect.

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 2024.01 of the Handbook