Unit convenor and teaching staff |
Unit convenor and teaching staff
Lecturer/Convener
Hassan Doosti
Contact via Email
Room 534, 12 Wally's Walk
Please refer to iLearn for Consultation hours.
Lecturer/Convener
Nan Zou
Contact via Email
Room 606, 12 Wally’s Walk
Please refer to iLearn for Consultation hours.
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Credit points |
Credit points
10
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Prerequisites |
Prerequisites
STAT6170 or STAT670
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Corequisites |
Corequisites
STAT6180 or STAT680
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Co-badged status |
Co-badged status
This unit is co-badged STAT2114.
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Unit description |
Unit description
This unit provides an introduction to survey design and experimental design. In survey design we look at different sampling strategies and analysis of population estimates. In experimental design we learn how to construct basic designs as well as the statistical methods available for analysis. Real life applications are used.
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Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
HURDLES: No hurdle requirements
ASSIGNMENT SUBMISSION: Assignment submission will be online through the iLearn page.
Submit assignments online via the appropriate assignment link on the iLearn page. A personalised cover sheet is not required with online submissions. Read the submission statement carefully before accepting it as there are substantial penalties for making a false declaration.
You may submit as often as required prior to the due date/time. Please note that each submission will completely replace any previous submissions. It is in your interests to make frequent submissions of your partially completed work as insurance against technical or other problems near the submission deadline.
LATE SUBMISSION OF WORK:
Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark of the task) will be applied for each day a written report or presentation assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted. The submission time for all uploaded assessments is 11:55 pm. A 1-hour grace period will be provided to students who experience a technical concern.
For any late submission of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, please apply for Special Consideration.
Assessments where Late Submissions will be accepted
In this unit, late submissions will accepted as follows:
Assignments 1 and 2 – YES, Standard Late Penalty applies
Online Mid-Semester Test- NO, unless Special Consideration is Granted
SPECIAL CONSIDERATION:
The Special Consideration Policy aims to support students who have been impacted by short-term circumstances or events that are serious, unavoidable and significantly disruptive, and which may affect their performance in assessment. If you experience circumstances or events that affect your ability to complete the written assessments in this unit on time, please inform the convenor and submit a Special Consideration request through ask.mq.edu.au.
FINAL EXAM POLICY: It is Macquarie University policy not to set early examinations for individuals or groups of students. All students are expected to ensure that they are available until the end of the teaching semester, that is, the final day of the official examination period. The only excuse for not sitting an examination at the designated time is because of documented illness or unavoidable disruption. In these special circumstances, you may apply for special consideration via ask.mq.edu.au.
If you receive special consideration for the final exam, a supplementary exam will be scheduled in the interval between the regular exam period and the start of the next session. By making a special consideration application for the final exam you are declaring yourself available for a resit during this supplementary examination period and will not be eligible for a second special consideration approval based on pre-existing commitments. Please ensure you are familiar with the policy prior to submitting an application.
You can check the supplementary exam information page on FSE101 in iLearn (bit.ly/FSESupp) for dates, and approved applicants will receive an individual notification one week prior to the exam with the exact date and time of their supplementary examination.
Name | Weighting | Hurdle | Due |
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Assignment 1 | 15% | No | Week 4 |
Mid-Semester Test | 15% | No | Week 7 |
Assignment 2 | 15% | No | Week 12 |
Final Exam | 55% | No | Formal Examination Period |
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 14 hours
Due: Week 4
Weighting: 15%
An assignment is set for students to complete independently, applying the knowledge gained from lectures, SGTA exercises, and their readings, and using statistical software. They will be made available on iLearn.
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 14 hours
Due: Week 7
Weighting: 15%
An online test will be made available on iLearn.
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 14 hours
Due: Week 12
Weighting: 15%
An assignment is set for students to complete independently, applying the knowledge gained from lectures, SGTA exercises, and their readings, with or without using statistical software. They will be made available on iLearn.
Assessment Type 1: Examination
Indicative Time on Task 2: 34 hours
Due: Formal Examination Period
Weighting: 55%
An examination held during the University’s formal examination period.
1 If you need help with your assignment, please contact:
2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation
The unit is delivered by lectures (2 hours per week, starting in Week 1) and SGTAs (1 hour per week, starting in Week 2). All teaching material will be available on iLearn.
SGTA exercises will be available from iLearn prior to the SGTA. Students are expected to have attempted these prior to the SGTA. Solutions will be explained, with emphasis on any area students had trouble with. At the end of the week, these solutions will then be placed on iLearn. The web address is https://ilearn.mq.edu.au.
Lecture notes will be made available on the unit iLearn page (https://iLearn.mq.edu.au/).
Recommended text:
Lohr, Sharon L (2019). Sampling: Design and Analysis, Second Edition, Boca Raton, FL : CRC Press, for Survey Design.
These are available from the Co-Op Bookshop and the University library.
Other useful references (available in library Reserve):
Kuehl, R.O. (2000 or newer). Statistical Principles of Research Design and Analysis, Second edition, Duxbury Press.
Lindman HR (1992). Analysis of Variance in Experimental Design.
Montgomery DC. (2019). Design and Analysis of Experiments, 10th Edition, Wiley.
Neter J, Wasserman W and Kutner M. (2004). Applied Linear Statistical Models.
Scheaffer RL, Mendenhall W and Ott RL (1996). Elementary Survey Sampling, 5th (or newer) Edition.
Cochran WG (1977). Sampling Techniques.
Moser CA & Kalton G (1971). Survey Methods in Social Investigations.
Barnett V (1974). Elements of Sampling Theory.
Software: We are using R through Rstudio in teaching this unit. R and Rstudio are free software and are widely used nowadays by statisticians. Students need to practice how to use the software and be expected to use R for the assignment. Students should also note that the test and the final examination may contain inline R codes and output that students need to interpret to answer the questions.
Survey design:
Week |
Topic |
1 |
Introduction to surveys: sample survey and its principal steps, probability and non-probability sampling, and sources of error |
2 |
Simple random sampling (SRS); Parameter estimation |
3 |
SRS (contd): estimation of proportion; Stratified random sampling |
4 |
Stratified random sampling (contd); Choosing strata sample sizes |
5 |
Ratio and regression estimators |
6 |
Cluster sampling; Systematic sampling |
Experimental design:
Week |
Topic |
7 |
Designed experiments vs observational studies; Completely randomized design (CRD): one-way ANOVA |
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Session 2 Break |
8 |
One-way ANOVA (contd) |
9 |
Contrasts (contd); Multiple comparisons; |
10 |
Model checking |
11 |
More on CRD; Randomized block design (RBD) |
12 |
The analysis of covariance |
Week 13: Revision (self-study and exam preparation)
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.
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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 ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au
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.
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
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Macquarie University offers a range of Student Support Services including:
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Unit information based on version 2023.03 of the Handbook