- Class Number 8326
- Term Code 2960
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- Karuna Reddy
- Karuna Reddy
- Class Dates
- Class Start Date 22/07/2019
- Class End Date 25/10/2019
- Census Date 31/08/2019
- Last Date to Enrol 29/07/2019
This course is designed to equip participants with the necessary skills to analyse large survey data sets to answer research and policy questions. Students will be introduced to a number of multivariate statistical methods for analysing numeric, categorical and censored data as well as techniques for analysing event-history data. Methods covered include multinomial logistic regression, survival analysis and cox regression. Participants will use a major computer statistical software package such as Stata to apply the methods to survey data and to interpret and discuss the results of their data analysis.
Upon successful completion, students will have the knowledge and skills to:Upon successful completion of this course, students will have the knowledge and skills to:
- Construct a research question using theory and data
- Justify the use of a particular technique
- Present and interpret statistical research results
- Use statistical software such as Stata to conduct a range of multivariate statistical techniques
This course aims to equip participants with the necessary skills to analyse large survey data sets to answer research and policy questions. Students will be introduced to a number of statistical methods for analysing numeric/continuous, categorical and ordered data as well as techniques for analysing event-history data. Methods covered include logistic regression and multivariate statistical analysis. Participants will learn to use a computer statistical software package such as Stata to apply the methods to survey data and to interpret and discuss the results of their data analysis. Teaching is provided through lectures, tutorials, and computer training sessions. This course will provide students with the skills necessary to undertake or assess, complex quantitative research.
Access to the ANU Wattle learning management system is required for this unit. All relevant resources will be provided in class or through the Wattle page for this course.
Students will be given feedback in the following forms in this course:
- written comments
- verbal comments
- feedback to whole class, groups, individuals, focus group etc
ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.
|Week/Session||Summary of Activities||Assessment|
|1||Data, types, survey data sources, summary statistics, graphs.|
|2||Univariate and bivariate analysis. Introduction to survey data modelling, simple linear regression, assumptions, diagnostics.|
|3||Multiple linear regression||Quiz 1 (due date: 9/8/2019)|
|4||Interaction effects, dummy variables.|
|5||Non-Gaussian models: logistic models.|
|6||Preparing your poster.|
|7||Non-Gaussian models: logistic models, with dummy and interaction effects.|
|8||Non-Gaussian models: multinomial models.||Quiz 2 (due date: 27/9/2019)|
|9||Non-Gaussian models: ordinal logistic models, Poisson models.|
|10||Introduction to multivariate analysis: Principal components and Factor Analysis.|
|11||Poster presentation||Quiz 3 (due date: 14/10/2019)|
|12||Poster presentation||Poster submission (due date: 7/11/2019)|
Required depending on the class enrolment number
|Assessment task||Value||Due Date||Return of assessment||Learning Outcomes|
|Quiz 1||5 %||09/08/2019||19/08/2019||1, 2|
|Quiz 2||10 %||27/09/2019||07/10/2019||1, 2, 3|
|Quiz 3||15 %||14/10/2019||24/10/2019||1, 2, 3, 4|
|Poster presentation||40 %||23/10/2019||28/11/2019||1, 2, 3, 4|
|Take home exercise||30 %||07/11/2019||28/11/2019||1, 2, 3, 4|
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:
The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.
Moderation of Assessment
Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.
Assessment Task 1
Learning Outcomes: 1, 2
This is an online quiz worth 5%. The learning outcomes are linked to the first two lectures.
Assessment Task 2
Learning Outcomes: 1, 2, 3
This is an online quiz worth 10% and involves lessons from 3 weeks. The learning outcomes are linked to lectures 3-5.
Assessment Task 3
Learning Outcomes: 1, 2, 3, 4
This is an online quiz worth 15% and involves lessons from 4 weeks. The learning outcomes are linked to lectures 7-10.
Assessment Task 4
Learning Outcomes: 1, 2, 3, 4
This is worth 40% (split by the actual powerpoint presentation and hard-copy poster submission) and involves the application of all the methods and techniques learned throughout the 10 weeks of lectures.
Assessment Task 5
Learning Outcomes: 1, 2, 3, 4
Take home exercise
This is worth 30% and is the final assessment in the course. The learning outcomes are linked to all 10 weeks of lectures.
Academic integrity is a core part of the ANU culture as a community of scholars. At its heart, academic integrity is about behaving ethically, committing to honest and responsible scholarly practice and upholding these values with respect and fairness.
The ANU commits to assisting all members of our community to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to be familiar with the academic integrity principle and Academic Misconduct Rule, uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with.
The Academic Misconduct Rule is in place to promote academic integrity and manage academic misconduct. Very minor breaches of the academic integrity principle may result in a reduction of marks of up to 10% of the total marks available for the assessment. The ANU offers a number of online and in person services to assist students with their assignments, examinations, and other learning activities. Visit the Academic Skills website for more information about academic integrity, your responsibilities and for assistance with your assignments, writing skills and study.
You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.
For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.
Individual assessment tasks may or may not allow for late submission. Policy regarding late submission is detailed below:
- Late submission not permitted. If submission of assessment tasks without an extension after the due date is not permitted, a mark of 0 will be awarded.
- Late submission permitted. Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.
Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.
Assignments will be returned electronically via the Wattle system or presented in class.
Extensions and Penalties
Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. The Course Convener may grant extensions for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.
Resubmission of Assignments
Resubmission of assignments is not allowed in this course.
Distribution of grades policy
Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.
Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.
Support for students
The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).
- ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
- ANU Diversity and inclusion for students with a disability or ongoing or chronic illness
- ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
- ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
- ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
- ANUSA supports and represents undergraduate and ANU College students
- PARSA supports and represents postgraduate and research students
Sampling theory; optimum stratification of populations; sample allocations in various sampling survey methods; data mining; statistical data analysis of samples and surveys; R package development