• Class Number 2499
  • Term Code 2930
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Ian McDermid
    • Ian McDermid
  • Class Dates
  • Class Start Date 25/02/2019
  • Class End Date 31/05/2019
  • Census Date 31/03/2019
  • Last Date to Enrol 04/03/2019
SELT Survey Results

STAT3012 is a course that deals with two of the most important approaches to collecting research data - surveys and experiments.

The first half of the course will focus on experimental design and will cover topics such as the analysis of variance; the completely randomised design; the randomized complete block design; Latin squares; factorial designs; and if time permits nested designs.

Survey sampling topics will be covered in the second half of the course and may include: simple random sampling, with and without replacement; estimation of population total, mean and proportion; subpopulation inference; systematic sampling; stratified sampling; ratio estimation; unequal probability sampling, including the Hansen and Hurwitz estimator and the Horvitz-Thompson estimator; regression estimation; and estimation of population size.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Select and design an appropriate method of data collection for a research project.
  2. Apply statistical survey sampling techniques to design a routine sample survey.
  3. Devise and apply suitable estimation procedures to analyse the results of a routine sample survey.
  4. Apply basic principles in the design of simple experiments.

Research-Led Teaching

My teaching in this course in statistical design and modelling will draw on numerous examples from my extensive experience in applied statistical research and consulting.

Field Trips

Not relevant in this course.

Additional Course Costs

The application of modern statistical techniques requires familiarity with some statistical computing package and the assignments for this course will require some analysis on a computer. This course makes extensive use of the R computing package, which is freely available to download at http://www.r-project.org. Further instructions on R, including a series of revision workshops will be made available on the Wattle site for this course. R is also available on all InfoCommons computers on the ANU campus. All tutorials for this course will be held as Computer Laboratories in one of the InfoCommons PC laboratories, though you may also find it helpful to also bring a laptop with R installed to the tutorials.

Examination Material or equipment

No electronic aids are permitted (e.g. laptops, phones), but you will need a calculator (which may be programmable, but not one that can connect to the internet).

Unannotated paper-based dictionary (no approval required).

One A4 page with notes on both sides.

Required Resources

Class materials, including detailed lecture notes, slides, lecture demonstrations, tutorials, assignments and other relevant materials, will be made available on the class web page on Wattle.

Lawson, John (2015) Design and Analysis of Experiments with R, (ANU Library INTERNET RES)

Lohr, Sharon L. (2010) Sampling Design and Analysis, 2nd Edn (ANU CHIFLEY HA31.2.L64 2010, ebook requested for INTERNET RES)

Staff Feedback

Students will be given feedback in the following forms in this course:

  • individual feedback will be provided by your tutor, who will mark your assignments. Solutions to the assignments will be provided on Wattle and discussed in tutorials and/or lectures.
  • you are also welcome to ask questions of me or your tutor at consultations or during classes. If you wish to ask me questions immediately following a class, please wait for me outside the classroom, so that I can clean-up and log-off in preparation for the next class that will be using the same venue.
  • I am also happy to answer short questions on the course material sent via email or posted on Wattle. If you send me a question via email, I will (unless you specifically ask me not to) post your question (anonymously) and my answer on Wattle for the benefit of all students.

Student Feedback

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.

Other Information


If moderation of marks is required, then marks may be scaled. Your final mark for the course will be based on the raw marks allocated for each of your assessment items. However, your final mark may not be the same number as produced by that formula, if marks are scaled. Any scaling applied will be restricted to your course code (not across different co-taught courses) and will preserve the rank order of raw marks (i.e. if your raw mark exceeds that of another student, then your scaled mark will exceed or be the same as the scaled mark of that student), and may be either up or down.

Communication and Announcements

If the lecturer or anyone in the School, College or University administration, need to contact you, we will do so via your official ANU student email address, which you need to check regularly. Information from the Registrar and Student Services’ office will also be sent to this email address.

You are also expected to check the course Wattle site regularly for announcements about this course, e.g. changes to timetables or notifications of cancellations.

Class Schedule

Week/Session Summary of Activities Assessment
1 Overview of data collection methods. Introduction to experimental design.
2 Analysis of variance (ANOVA). Completely randomised designs.
3 Blocking in the design of experiments.
4 Factorial experimental designs.
5 More complex experimental designs. Assignment 1
6 Introduction to survey methods. Simple random sampling. Mid-semester exam
7 Proportions, ratios and sub-population inference.
8 Systematic sampling.
9 Stratification.
10 Ratio estimation.
11 Regression estimators. Assignment 2
12 More complex topics in survey design.
13 End of semester examination period Final exam

Tutorial Registration

Tutorial registration will be via the course Wattle site.

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Assignment 1 (Experiments) 15 % 29/03/2019 04/04/2019 1, 4
Mid-semester Exam (Experiments) 25 % 01/04/2019 09/05/2019 1, 4
Assignment 2 (Surveys) 25 % 23/05/2019 30/05/2019 1, 2, 3
Final Exam (Surveys) 35 % 06/06/2019 04/07/2019 1, 2, 3

* 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:

Assessment Requirements

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. Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.

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.


Will not be assessed, but attendance and participation, especially at the workshops and tutorials (computer labs) is strongly recommended.


See assessment tasks 2 and 4, above. Apart from learning outcome 1, which will be assessed in both examinations, the mid-semester exam will concentrate on experiments (learning outcome 4) and the final exam will concentrate on surveys (learning outcomes 2 and 3).

Assessment Task 1

Value: 15 %
Due Date: 29/03/2019
Return of Assessment: 04/04/2019
Learning Outcomes: 1, 4

Assignment 1 (Experiments)

Detailed assignment specifications will be handed out at least three weeks prior to the due date. Assignment may involve some group work and will definitely involve using R to analyze data from a case study, then editing the R output and preparing a written report on your analyses.

Worth 15% of the overall assessment. Note that this is an applied statistics course and the assignments represent an opportunity for you to show that you can correctly apply the statistical techniques. So this assignment is compulsory and the marks are NOT redeemable on the mid-semester exam.

Assessment Task 2

Value: 25 %
Due Date: 01/04/2019
Return of Assessment: 09/05/2019
Learning Outcomes: 1, 4

Mid-semester Exam (Experiments)

2 hour formal examination to be scheduled during the mid-semester exam period (weeks 6 and 7).

Worth 25% of the overall assessment. This exam is compulsory and the marks are NOT redeemable on the final exam, which addresses different learning outcomes.

Assessment Task 3

Value: 25 %
Due Date: 23/05/2019
Return of Assessment: 30/05/2019
Learning Outcomes: 1, 2, 3

Assignment 2 (Surveys)

Detailed assignment specifications will be handed out at least three weeks prior to the due date. Assignment may involve some group work and will definitely involve using R to analyze data from a case study, then editing the R output and preparing a written report on your analyses.

Worth 25% of the overall assessment. Note that this is an applied statistics course and the assignments represent an opportunity for you to show that you can correctly apply the statistical techniques. So this assignment is compulsory and the marks are NOT redeemable on the final exam.

Assessment Task 4

Value: 35 %
Due Date: 06/06/2019
Return of Assessment: 04/07/2019
Learning Outcomes: 1, 2, 3

Final Exam (Surveys)

3 hour formal examination to be scheduled during the end of semester exam period.

Worth 35% of the overall assessment.

Academic Integrity

Academic integrity is a core part of our culture as a community of scholars. At its heart, academic integrity is about behaving ethically. This means that all members of the community commit to honest and responsible scholarly practice and to upholding these values with respect and fairness. The Australian National University commits to embedding the values of academic integrity in our teaching and learning. We ensure that all members of our community 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 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 University has policies and procedures in place to promote academic integrity and manage academic misconduct. Visit the following Academic honesty & plagiarism website for more information about academic integrity and what the ANU considers academic misconduct. The ANU offers a number of services to assist students with their assignments, examinations, and other learning activities. The Academic Skills and Learning Centre offers a number of workshops and seminars that you may find useful for your studies.

Online Submission

You are encouraged to submit assignments online through Turnitin, which will require you to electronically sign a declaration as part of the submission of your assignment. If group work is involved, then assignments may be submitted by just one member of the group, but must include a completed cover sheet clearly identifying all members of the group. Please keep a copy of the assignment for your records.

Hardcopy Submission

You may choose not to submit your assignments through Turnitin. If you choose this option, you will be required to submit your assignment report (and copies of all references included in the assignment report) in hard copy by the due date. All submitted hard copy assignments must include a completed a completed cover sheet clearly identifying all members of your group. Please keep a copy of the assignment for your records.

Late Submission

No submission of assessment tasks without an extension after the due date will be permitted. If an assessment task is not submitted by the due date, a mark of 0 will be awarded.

Referencing Requirements

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.

Returning Assignments

Assignments will be marked to a commonly agreed marking schedule by your tutor and returned to you online or in tutorials. Assignment solutions will be discussed in the tutorials in the first teaching week following the due date.

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

There will be no resubmission of assignments.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

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).

Ian McDermid
02 612 51084

Research Interests

Over 30 years experience in statistical consulting, research and teaching. My current research interests are in: population health and mortality; sample survey analysis and design.

Ian McDermid

Tuesday 14:30 16:00
Ian McDermid

Research Interests

Ian McDermid

Tuesday 14:30 16:00

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions