• Class Number 2334
  • Term Code 3030
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
  • COURSE CONVENER
    • Ian McDermid
  • LECTURER
    • Ian McDermid
  • Class Dates
  • Class Start Date 24/02/2020
  • Class End Date 05/06/2020
  • Census Date 08/05/2020
  • Last Date to Enrol 02/03/2020
SELT Survey Results

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

The first part 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 part of the course and may include: simple random sampling, with and without replacement; estimation of population total, mean, proportion and size; subpopulation inference; systematic sampling; stratified sampling; ratio estimation; regression estimation; unequal probability sampling, including the Hansen and Hurwitz estimator and the Horvitz-Thompson estimator; regression estimation; and if time permits, cluster sampling.

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 basic principles in the design of simple experiments;
  3. Apply statistical survey sampling techniques to design a routine sample survey; and
  4. Devise and apply suitable estimation procedures to analyse the results of a routine sample survey.

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 be provided with a calculator (HP Scientific Calculator 300s+ ) for use in exams. Only calculators provided by the Examinations Office on the day of the exam are permitted in the exam room.

You will also have access to a CBE issued dictionary (Australian Mini Oxford dictionary, fourth edition).

One A4 page with hand-written 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 (which is shared with the co-taught courses, STAT4029 and STAT7029). It is essential you visit the class Wattle site regularly, but you will need to be correctly enrolled in the course before you can access the Wattle site.

There will be a lot of detailed material available on Wattle, so there is NO prescribed text for this course.

I do recommend the following texts, and more references and recommendations will be made as the course progresses:

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 Library INTERNET RES or 1 hard copy CHIFLEY HA31.2.L64 2010)

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

Enrolment and Requisites

This is a course in applied statistics, using numerous examples, rather than a course in mathematical statistics; but it is NOT an introductory first course in statistics. We assume you have already completed a course such as STAT2008 Regression Modelling as an essential prerequisite AND that you have also completed the equivalent of an introductory course in basic statistics (such as STAT1003 or STAT1008) that is an essential prerequisite to the STAT2008 course.

If you have not completed the compulsory ANU prerequisite course (STAT2008 or STAT2014), you will not be able to enrol in STAT3012. If you have completed an equivalent course elsewhere, you should contact the RSFAS Office with appropriate evidence, for a permission code to enrol in STAT3012. Only the Director of Education for RSFAS can approve the issuing of permission codes for STAT courses, so please contact the Office, not the course convenor.

To assist with the more mathematical parts of the course, recent completion or concurrent enrolment in a course in mathematical statistics such as STAT2001 Introductory Mathematical Statistics is also a strongly recommended co-requisite.

The course also uses the R statistical package, which applies matrix algebra to implement the statistical techniques. An understanding of matrix algebra (equivalent to an

introductory mathematics course such as MATH1113) would be helpful in understanding how the R routines work, but such knowledge is not a required prerequisite nor an

examinable part of this course.


Scaling

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 course instructors 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 Introduction to data collection and the design of experiments. Weekly tutorials commence
2 Completely randomised experimental designs and the Analysis of Variance (ANOVA).
3 Blocking and random effects.
4 Factorial experimental designs.
5 Confounding and other advanced topics in experimental design. Assignment 1 due
6 Introduction to survey methods and simple random sampling. Mid-semester exam (weeks 6 or 7)
7 Proportions, ratios and sub-population inference.
8 Systematic sampling.
9 Stratification (and cluster sampling).
10 Ratio estimation.
11 Regression estimators. Assignment 2 due
12 Other topics in survey design.

Tutorial Registration

Please see Wattle for details of the course tutors and up to date information on consultation arrangements.

Tutorial signup for this course will be done via the Wattle website. Detailed information about signup times will be provided on Wattle.

When tutorials are available for enrolment, follow these steps:

1. Log on to Wattle, and go to the course site.

2. Click on the link “Tutorial enrolment”

3. On the right of the screen, click on the tab “Become Member of ……” for the tutorial class you wish to enter.

4. Confirm your choice

If you need to change your enrolment, you will be able to do so by clicking on the tab “Leave group…” and then re-enrol in another group. You will not be able to enrol in groups that have reached their maximum number.

Please note that enrolment in ISIS must be finalised for you to have access to Wattle.

Contact the RSFAS Office if you have any problems enrolling in a tutorial.

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Assignment 1 (Experiments) 15 % 27/03/2020 03/04/2020 1, 2
Mid-semester Exam (Experiments) 25 % 30/03/2020 08/05/2020 1, 2
Assignment 2 (Surveys) 25 % 22/05/2020 29/05/2020 1, 3, 4
Final Exam (Surveys) 35 % 04/06/2020 02/07/2020 1, 3, 4

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

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. 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.

Participation

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

Examination(s)

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 2) and the final exam will concentrate on surveys (learning outcomes 3 and 4).

Assessment Task 1

Value: 15 %
Due Date: 27/03/2020
Return of Assessment: 03/04/2020
Learning Outcomes: 1, 2

Assignment 1 (Experiments)

Detailed assignment specifications will be made available on Wattle at least three weeks prior to the due date. Assignment may be done individually or in student-selected groups 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: 30/03/2020
Return of Assessment: 08/05/2020
Learning Outcomes: 1, 2

Mid-semester Exam (Experiments)

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

This will be a centrally administered examination through Examinations, Graduations & Prizes and will be timetabled prior to the examination period.

Please check ANU Timetabling for further information. Further information about the examination will be provided in class and on Wattle by no later than week 5.

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: 22/05/2020
Return of Assessment: 29/05/2020
Learning Outcomes: 1, 3, 4

Assignment 2 (Surveys)

Detailed assignment specifications will be made available on Wattle at least three weeks prior to the due date. Assignment may be done individually or in student-selected groups 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: 04/06/2020
Return of Assessment: 02/07/2020
Learning Outcomes: 1, 3, 4

Final Exam (Surveys)

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

This will be a centrally administered examination through Examinations, Graduations & Prizes and will be timetabled prior to the examination period.

Please check ANU Timetabling for further information. Further information about the examination will be provided in class and on Wattle by no later than week 12.

Worth 35% of the overall assessment.

Academic Integrity

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.

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. Extensions may be granted 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
ian.mcdermid@anu.edu.au

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 14:00 15:30
Ian McDermid
x51084
ian.mcdermid@anu.edu.au

Research Interests


Ian McDermid

Tuesday 14:00 15:30

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