Course overview
- Study period
- Semester 2, 2024 (22/07/2024 - 18/11/2024)
- Study level
- Postgraduate Coursework
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Social Science School
Quantitative research methods are the most commonly used research methods in the social sciences. They are widely used by academic researchers, government agencies, private companies, and community organisations. This course provides an introduction to quantitative methods in the social sciences. It emphasises how social scientists use simple quantitative techniques to investigate research questions coming from social science theory, prior research and applied problems. The course focuses on the link between theory and research in social science, the logic of quantitative empirical analysis, and techniques for describing quantitative data and drawing inferences (generalisations) about larger populations. The course also introduces Jamovi statistical software for simple quantitative analysis.
SOCY7339 is an introduction to social statistics course that emphasises both statistical concepts as well as working with data. It provides the foundational concepts and skills for more advanced courses in quantitative methods.
The course is divided into three main parts:
- Introductory material. This section introduces key ideas of quantitative social research including the elements of the research process, and the roles of theorisation, conceptualisation and measurement.
- Descriptive statistics. This material introduces you to simple methods for describing the characteristics of a single variable and examining relationships between two or more variables.
- Statistical inference. This topic provides you with a conceptual introduction to basic ideas of statistical inference, the manner in which we use information taken from a probability sample to draw conclusions (inferences) about the larger population from which the sample is drawn. It introduces some simple techniques for drawing inferences about means and tabulated variables.
SOCY7339 is cumulative. Material in later sections of the course builds directly on material covered in earlier weeks. If you do not keep up it will be easy to fall behind. On the other hand, if you keep up with the weekly tutorial activities this course will be fun and and useful. This course is taught alongside an undergraduate offering.
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Course requirements
Assumed background
SOCY7339ᅠdoes not assume any prior background in social statistics or data analysis.
Incompatible
You can't enrol in this course if you've already completed the following:
PSYC1040 (only if the course was completed in 2022 or 2023), SOCY2339, SOCY2120, SOCY2059, SOCY7069, SO320, SO321, SO420, SO421
Course contact
School enquiries
Level 3, Michie Building (09), St Lucia campus, The University of Queensland.
Monday-Friday, 9:00am-12:00pm, 1:00pm-4:00pm.
Course staff
Lecturer
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
The purpose of SOCY2339ᅠis to provide students with an accessible, structured introduction to the basic statistical concepts and techniques of quantitative methods in social science.ᅠ It also aims to give students skills in simple data analysis, using Jamovi statistical software. Quantitative skills are important for both researchers and non-researchers. Basic quantitative skills allows you to read and understand a range of different sources of data - especially those we come across in everyday use, AND engage critically with them.ᅠ
This course provides excellent foundational knowledge for SOCY3039 whichᅠtakes your statistical trainingᅠto the next level. Together, these courses allow you to build a strong foundation in research methods, data analysis, and comfort in working with numbers. This is highly desirable for students wanting to do an honours degree in Sociology and Criminology. Ability to workᅠwith data isᅠalso a highly transferable and desirable skillᅠfor theᅠworkplace.ᅠ
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Understand the stages of quantitative research
LO2.
Understand how social theories are related to social scientific concepts
LO3.
Be able to calculate and interpret basic univariate descriptive statistics
LO4.
Be able to construct and interpret two and three-way cross-tabulations
LO5.
Understand the logic of classical statistical inference
LO6.
Be able to make statistical inferences based on a sample mean/proportion or comparison of means/proportions
LO7.
Be able to carry out a chi-squared test of statistical independence for tabular data
LO8.
Be able to construct and interpret a correlation coefficient
LO9.
Appreciate the logic of bivariate linear regression
LO10.
Be able to use Jamovi statistical software to access and manipulate survey data in preparation for quantitative analysis
LO11.
Be able to use Jamovi statistical software to carry out simple descriptive and inferential statistical procedures.
Assessment
Assessment summary
Category | Assessment task | Weight | Due date |
---|---|---|---|
Computer Code, Paper/ Report/ Annotation | Assignment 1 - Applying Descriptive Statistics | 40% |
9/09/2024 2:00 pm |
Computer Code, Paper/ Report/ Annotation | Assignment 2 - Applying Inferential Statistics | 40% |
25/10/2024 2:00 pm |
Examination |
Tests
|
20% |
5/08/2024 - 10/10/2024
Each review quiz is due the week after it is assigned: Quiz 1 (week 3) will be open Monday 5th August 2pm, due date 7th August 2pm. Quiz 2 (week 6) will be open Monday 26th August 2pm, due date 28th August 2pm. Quiz 3 (week 9) will be open Monday 16th September 2pm, due date 18th September 2pm. Quiz 4 (week 11) will be open Monday 7th October 2pm, due date 10th October 2pm. |
Assessment details
Assignment 1 - Applying Descriptive Statistics
- Mode
- Written
- Category
- Computer Code, Paper/ Report/ Annotation
- Weight
- 40%
- Due date
9/09/2024 2:00 pm
- Learning outcomes
- L02, L03, L04
Task description
This assessment item consists of a mix of statistics/data analysis problems that must be completed using STATA software for analysis or calculations by hand. The assessment will be posted to Blackboard on Tuesday of Week 3, and are due on Friday September 9th at 2pm.
You must upload your assignment as one file that contains three parts to a Blackboard link. Part A includes a section on hand calculations. Part B includes a section on Jamovi based exercises. Part C is a statement of transferable skills.
Part A focuses on manual calculations (5 questions total)
Part B focuses on Jamovi calculations (10 questions total)
Part C focuses on real world application and definitions (4 questions total)
Marking criteria and/or marking rubrics are available in the ‘Assessment’ folder in Blackboard for this course.
AI use: This assessment task evaluates student’s abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
You must submit your assignment electronically by the due time, on the due date.
Your assignment must be submitted via Turnitin on blackboard. To submit your assignment electronically log in to http://learn.uq.edu.au/ with your UQ username and password, then click on Course Code>>Assessment>>Assignments, and use the appropriate assignment submission link for each piece of assessment. No e-mailed submissions of assessments will be accepted.
Turnitin links will be configured to permit early submission of assessment items. Students will have the opportunity to submit draft assignments to Turnitin prior to submission of the final assignment in order to review similarity index content and to improve academic writing practice in accordance with UQ Academic Integrity policies.
By uploading your assignment via Turnitin, you are certifying that the work you submit is your own work except where correctly attributed to another source. Do not submit your assignment if it contains any work that is not your own. Please note that on the preview page, your assignment will be shown without formatting. Your assignment will retain formatting and your coordinator/tutor will be able to see formatted assignments. Once you have submitted your assignment you are able to go back and view your submission with the correct formatting.
You are required to retain proof of submission of your assessment. Your Digital Receipt is available for download from your Assignment Dashboard. If you cannot see your submission and download your digital receipt, your assessment has not been successfully submitted, please submit again. If you are unable to submit your assignment by the due date, you need to apply for an extension as set out in section 5.3.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
An extension request without penalty will only be considered under exceptional circumstances as outlined on my.UQ. You must submit the extension request as soon as it becomes evident that an extension is needed, but no later than the assessment item submission due date.
A request for an extension to an assessment due date must be accompanied by supporting documentation corroborating the reason for the request. The student submitting the request is fully responsible for all supporting documentation that is provided with the request and should ensure all documents are authentic.
Extensions on the basis of an approved Student Access Plan (SAP) or an Extension Verification Letter (EVL) can be approved for a maximum period of 7 calendar days. Extensions exceeding this duration or subsequent extensions for a piece of assessment will require additional supporting documentation (e.g., a medical certificate or other supporting evidence listed on my.UQ) and Course Coordinator approval.
When you submit an extension request in the student portal, it is received, read, and actioned by the Social Science Student Administration Team. It does not go to the course coordinator.
Late applications (requests received after the assessment item submission due date) must include evidence of the reasons for the late request, detailing why you were unable to apply for an extension by the due date.
In considering applications for extensions, students may be asked to supply the work they have completed to date on the assessment piece. This is to establish what efforts have already been made to complete the assessment, and whether the proposed work plan is feasible.
Late submissions of extension requests in your final semester of study could delay your graduation by up to one semester.
Work can NOT be accepted if it is more than one week (7 calendar days) late without prior approval.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
10% of maximum mark will be deducted per day for late submission
Assignment 2 - Applying Inferential Statistics
- Mode
- Written
- Category
- Computer Code, Paper/ Report/ Annotation
- Weight
- 40%
- Due date
25/10/2024 2:00 pm
- Learning outcomes
- L05, L06, L07, L08, L09, L10, L11
Task description
This assessment item consists of a mix of statistics/data analysis problems that must be completed by hand and using Jamovi software for analysis. The computer exercises will be posted to Blackboard on Tuesday of Week 8, and is due on October 25th at 2pm.
You must upload your assignment as one file that contains three parts to a Blackboard link. Part A includes a section on hand calculations. Part B includes a section on Jamovi based exercises. Part C is a statement of transferable skills.
Part A focuses on manual calculations (3 questions total)
Part B focuses on Jamovi calculations (7 questions total)
Part C focuses on real world applications and definitions (4 questions total)
Marking criteria and/or marking rubrics are available in the ‘Assessment’ folder in Blackboard for this course.
AI use: This assessment task evaluates student’s abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
You must submit your assignment electronically by the due time, on the due date.
Your assignment must be submitted via Turnitin on blackboard. To submit your assignment electronically log in to http://learn.uq.edu.au/ with your UQ username and password, then click on Course Code>>Assessment>>Assignments, and use the appropriate assignment submission link for each piece of assessment. No e-mailed submissions of assessments will be accepted.
Turnitin links will be configured to permit early submission of assessment items. Students will have the opportunity to submit draft assignments to Turnitin prior to submission of the final assignment in order to review similarity index content and to improve academic writing practice in accordance with UQ Academic Integrity policies.
By uploading your assignment via Turnitin, you are certifying that the work you submit is your own work except where correctly attributed to another source. Do not submit your assignment if it contains any work that is not your own. Please note that on the preview page, your assignment will be shown without formatting. Your assignment will retain formatting and your coordinator/tutor will be able to see formatted assignments. Once you have submitted your assignment you are able to go back and view your submission with the correct formatting.
You are required to retain proof of submission of your assessment. Your Digital Receipt is available for download from your Assignment Dashboard. If you cannot see your submission and download your digital receipt, your assessment has not been successfully submitted, please submit again. If you are unable to submit your assignment by the due date, you need to apply for an extension as set out in section 5.3.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
An extension request without penalty will only be considered under exceptional circumstances as outlined on my.UQ. You must submit the extension request as soon as it becomes evident that an extension is needed, but no later than the assessment item submission due date.
A request for an extension to an assessment due date must be accompanied by supporting documentation corroborating the reason for the request. The student submitting the request is fully responsible for all supporting documentation that is provided with the request and should ensure all documents are authentic.
Extensions on the basis of an approved Student Access Plan (SAP) or an Extension Verification Letter (EVL) can be approved for a maximum period of 7 calendar days. Extensions exceeding this duration or subsequent extensions for a piece of assessment will require additional supporting documentation (e.g., a medical certificate or other supporting evidence listed on my.UQ) and Course Coordinator approval.
When you submit an extension request in the student portal, it is received, read, and actioned by the Social Science Student Administration Team. It does not go to the course coordinator.
Late applications (requests received after the assessment item submission due date) must include evidence of the reasons for the late request, detailing why you were unable to apply for an extension by the due date.
In considering applications for extensions, students may be asked to supply the work they have completed to date on the assessment piece. This is to establish what efforts have already been made to complete the assessment, and whether the proposed work plan is feasible.
Late submissions of extension requests in your final semester of study could delay your graduation by up to one semester.
Work can NOT be accepted if it is more than one week (7 calendar days) late without prior approval.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
10% of the maximum mark will be deducted per day for late submission
Tests
- Online
- Mode
- Written
- Category
- Examination
- Weight
- 20%
- Due date
5/08/2024 - 10/10/2024
Each review quiz is due the week after it is assigned:
Quiz 1 (week 3) will be open Monday 5th August 2pm, due date 7th August 2pm.
Quiz 2 (week 6) will be open Monday 26th August 2pm, due date 28th August 2pm.
Quiz 3 (week 9) will be open Monday 16th September 2pm, due date 18th September 2pm.
Quiz 4 (week 11) will be open Monday 7th October 2pm, due date 10th October 2pm.
- Learning outcomes
- L01, L02, L03, L04, L05, L09
Task description
In weeks 3, 6, 9 and 11 there will be tests that are designed to help you a) practice the materials learned in lecture, and b) make progress on your assignments. There are 4 tests to complete over the 12 week semester.
The tests can be found on the Blackboard site under the Assessment tab. They are to be submitted online no later than 48 hours from the time that the test is opened. For example, the test assigned for week 3 will open Monday 5th of August 2pm and will be due by Wednesday 7th August 2pm. Quiz 4 is opened for 72 hours, taking into account the Public Holiday (07 October). Tests are set up as online quizzes. Solutions will be made available on the blackboard site after the due date, and no late submissions will be accepted without prior approval from the course coordinator. If you are unable to complete the tests within the given period you will need to apply for a deferred exam no later than 5 calendar days after the due date.
The tests are not graded by the course coordinator or the tutors - they are graded automatically in blackboard. It is your responsibility to look at the answers provided. The tests are graded out of a total of questions across the semester answered correctly. These must be completed by the due dates. Each week, the number of questions will vary - some weeks might have 10 questions, others might have only 4 questions. This reflects the time needed to spend on each set of exercises.
Details about the tests will be provided in week 1 of the semester.
Marking criteria and/or marking rubrics are available in the ‘Assessment’ folder in Blackboard for this course.
AI use: This assessment task evaluates student’s abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Exam details
Planning time | no planning time minutes |
---|---|
Duration | 60 minutes |
Calculator options | Any calculator permitted |
Open/closed book | Open Book examination |
Materials | The tests will be completed online through blackboard. You can refer to your class notes but this must be your own work. No collusion is permitted. |
Exam platform | Learn.UQ |
Invigilation | Not invigilated |
Submission guidelines
Submissions are made online. Please see the Blackboard site for instructions (http://learn.uq.edu.au/).
You are required to retain proof of submission of your assessment. Your Digital Receipt is available for download from your Assignment Dashboard. If you cannot see your submission and download your digital receipt, your assessment has not been successfully submitted, please submit again.
Deferral or extension
You may be able to defer this exam.
The University recognises that on occasion a medical condition or other exceptional circumstances may impair your ability to attend an examination at the scheduled date and time. Depending on the circumstances, you may be eligible for a deferred examination, and be permitted to sit your in-class, mid-semester or end-of-semester examinations at a later scheduled time. For information on eligibility and application instructions, please view the following page on myUQ: Deferring an exam - my.UQ - University of Queensland
Course grading
Full criteria for each grade is available in the Assessment Procedure.
Grade | Cut off Percent | Description |
---|---|---|
1 (Low Fail) | 1 - 29 |
Absence of evidence of achievement of course learning outcomes. |
2 (Fail) | 30 - 44 |
Minimal evidence of achievement of course learning outcomes. |
3 (Marginal Fail) | 45 - 49 |
Demonstrated evidence of developing achievement of course learning outcomes |
4 (Pass) | 50 - 64 |
Demonstrated evidence of functional achievement of course learning outcomes. |
5 (Credit) | 65 - 74 |
Demonstrated evidence of proficient achievement of course learning outcomes. |
6 (Distinction) | 75 - 84 |
Demonstrated evidence of advanced achievement of course learning outcomes. |
7 (High Distinction) | 85 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. |
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Academic Integrity: All students must complete the Academic Integrity Modules https://www.uq.edu.au/integrity/
UQ Assignment Writing Guide: Steps for writing assignments - my.UQ - University of Queensland
Release of Marks: The marks and feedback for assessments will be released to students in a timely manner, prior to the due date of the next assessment piece for the course. This is with the exception of the final piece of assessment. The marks and feedback for the final assessment item will only be made available to the student on the Finalisation of Grades date at the end of semester.
Assessment Re-mark: For information on requesting an assessment re-mark, please view the following page on my.UQ: https://my.uq.edu.au/querying-result
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Library resources are available on the UQ Library website.
Additional learning resources information
Lecture notes will be available on Blackboard (under Learning Resources) for you to download in advance, the day before the lecture.ᅠ
ᅠ
In addition to the textbook, students should also bring to all computer lab sessions/online lab sessions:
- the computer lab worksheetsᅠ(available on the blackboard site)
- your lecture notes
- a USB flash drive.
These will be needed to complete the weekly lab exercises. Students will also need a calculator with basic arithmetic (plus, minus, multiply and divide) functions for the completion of exercises and assessment. A calculator will also be useful in lectures.ᅠ
ᅠ
You will be allowed to use approved calculators throughout the course.ᅠ
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Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
Learning period | Activity type | Topic |
---|---|---|
Week 1 (22 Jul - 28 Jul) |
Lecture |
WEEK 1 - Introduction to Course This introduces the course and describes the stages of social research, with an emphasis on quantitative research design. Learning outcomes: L01, L02 |
Practical |
NO TUTORIAL |
|
Week 2 (29 Jul - 04 Aug) |
Lecture |
WEEK 2 - Fundamentals of Quantitative Research Introduces the basics of measurement and the purpose of analysis. Learning outcomes: L01, L02, L03, L04 |
Practical |
Survey Materials, Codebooks and Raw Data Computer orientation - Understanding data sets Learning outcomes: L01, L03, L04, L10, L11 |
|
Week 3 (05 Aug - 11 Aug) |
Lecture |
WEEK 3 - Descriptive Statistics Descriptive statistics: mean, median, mode and measures of central tendency. Learning outcomes: L03, L06 |
Practical |
Jamovi Basics Orientation to Jamovi software. Learning outcomes: L01, L10, L11 |
|
Week 4 (12 Aug - 18 Aug) |
Lecture |
WEEK 4 - Graphical Representations of Data This lecture describes graphical ways of describing data. Learning outcomes: L01, L02, L03, L05 |
Practical |
NO TUTORIAL |
|
Week 5 (19 Aug - 25 Aug) |
Lecture |
WEEK 5 - Measures of Association This lecture introduces the concept of statistical measures of association including contigency tables and correlations Learning outcomes: L01, L03, L04, L05, L06, L07, L08 |
Practical |
Describing data Creating graphs and summary statistics in Jamovi with real world data Learning outcomes: L01, L02, L04, L10, L11 |
|
Week 6 (26 Aug - 01 Sep) |
Lecture |
WEEK 6 - Probability Theory This lecture will provide students with a a good foundation for statistics thorough basic probability theory. Essential for moving forward in the course! Learning outcomes: L01, L02, L06 |
Practical |
Measures of Association Cross tabs and correlations in Jamovi Learning outcomes: L01, L02, L10, L11 |
|
Week 7 (02 Sep - 08 Sep) |
Lecture |
WEEK 7 - Population and Sampling Distributions Lecture will continue the probability discussion to describe how probability is used in statistics. Learning outcomes: L01, L02, L06 |
Practical |
Recoding variables Create and recode existing variables into new ones. Examine missing variables and learn more about interpreting tables. Learning outcomes: L01, L10, L11 |
|
Week 8 (09 Sep - 15 Sep) |
Lecture |
WEEK 8 - Inferential Statistics: Confidence Intervals This lecture describes how information gathered from a sample can be inferred to the population. Includes the use of confidence intervals. Learning outcomes: L01, L07, L08 |
Practical |
Confidence Intervals Calculate and interpret confidence intervals using Jamovi Learning outcomes: L01, L05, L09, L10, L11 |
|
Week 9 (16 Sep - 22 Sep) |
Lecture |
WEEK 9 - Inferential Statistics: Hypothesis Tests This lecture describes how information gathered from a sample can be inferred to the population using hypothesis testing. Learning outcomes: L01, L02, L05, L09 |
Practical |
Hypothesis Testing Learn how to carry out and interpret a hypothesis test in Jamovi - single sample means and proportions. Learning outcomes: L01, L05, L08, L09, L10, L11 |
|
Week 10 (30 Sep - 06 Oct) |
Lecture |
WEEK 10 - Inferential Statistics: Large v Small Samples This lecture expands on the concepts of confidence intervals and hypothesis testing to include small samples and comparisons between groups. Learning outcomes: L01, L02, L05, L08, L09 |
Practical |
Hypothesis Tests for two groups Learn how to carry out hypothesis tests when you want to compare two groups in Jamovi Learning outcomes: L01, L02, L05, L08, L09, L10, L11 |
|
Week 11 (07 Oct - 13 Oct) |
Lecture |
WEEK 11 - The Chi Square Test This lecture reviews the material on measures of association and expands hypothesis test in order to test hypothesis between categorial variables. Learning outcomes: L01, L02, L05, L07, L08, L09 |
Practical |
Chi Square Learning how to find associations between categorial variables in Jamovi Learning outcomes: L01, L02, L05, L06, L07, L08, L09, L10, L11 |
|
Week 12 (14 Oct - 20 Oct) |
Lecture |
WEEK 12 - Bivariate Regression This lecture is dedicated to introducing the concept of regression analysis. Learning outcomes: L01, L02, L05, L08, L09 |
Practical |
Bivariate regression Basic bi-variate regression using Jamovi software. Learning outcomes: L01, L02, L05, L08, L09, L10, L11 |
|
Week 13 (21 Oct - 27 Oct) |
Lecture |
WEEK 13 - Using Statistics in the Real World Exploring where this knowledge can take you. Learning outcomes: L01, L02, L05, L09 |
Practical |
NO TUTORIALS |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.