Students

STAT2114 – Design of Surveys and Experiments

2024 – Session 2, In person-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Lecturer/Convener
Hassan Doosti
hassan.doosti@mq.edu.au
Contact via Email
Room 534, 12 Wally's Walk
Please refer to iLearn for Consultation hours.
Lecturer/Convener
Nan Zou
nan.zou@mq.edu.au
Contact via Email
Room 606, 12 Wally’s Walk
Please refer to iLearn for Consultation hours.
Credit points Credit points
10
Prerequisites Prerequisites
STAT170 or STAT1170 or STAT150 or STAT1250 or STAT171 or STAT1371
Corequisites Corequisites
STAT2170 or STAT2371 or BIOL2610 or PSYU2248
Co-badged status Co-badged status
This unit is co-badged STAT6114.
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.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Apply commonly used survey designs, sampling methods and appropriate statistical technique(s) to estimate population parameters based on a sample from each design.
  • ULO2: Identify potential issues in survey designs, such as sampling bias and non-sampling errors.
  • ULO3: Apply basic knowledge to design questionnaires and construct questions.
  • ULO4: Identify suitable experimental designs to solve a variety of problems.
  • ULO5: Identify appropriate statistical method(s) and use relevant software for the analysis of data from basic experimental designs.
  • ULO6: Evaluate the ethical relevance and implications in the design of a questionnaire and in the formulation of its questions.

General Assessment Information

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.

  • Assignment submission is via iLearn. You should upload this as a single scanned PDF file.
  • Please note the quick guide on how to upload your assignments provided on the iLearn page.
  • Please make sure that each page in your uploaded assignment corresponds to only one A4 page (do not upload an A3 page worth of content as an A4 page in landscape). If you are using an app like Clear Scanner, please make sure that the photos you are using are clear and shadow-free.
  • It is your responsibility to make sure your assignment submission is legible.
  • If there are technical obstructions to your submitting online, please email us to let us know.

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.

Assessment Tasks

Name Weighting Hurdle Due
Assignment 1 15% No Week 4
Online Mid-Semester Test 15% No Week 7
Assignment 2 15% No Week 12
Final Exam 55% No Formal Examination period

Assignment 1

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.

 
On successful completion you will be able to:
  • Apply commonly used survey designs, sampling methods and appropriate statistical technique(s) to estimate population parameters based on a sample from each design.
  • Identify potential issues in survey designs, such as sampling bias and non-sampling errors.
  • Apply basic knowledge to design questionnaires and construct questions.
  • Evaluate the ethical relevance and implications in the design of a questionnaire and in the formulation of its questions.

Online Mid-Semester Test

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 14 hours
Due: Week 7
Weighting: 15%

 

A test will be made available on iLearn.

 

 
On successful completion you will be able to:
  • Apply commonly used survey designs, sampling methods and appropriate statistical technique(s) to estimate population parameters based on a sample from each design.
  • Apply basic knowledge to design questionnaires and construct questions.
  • Identify appropriate statistical method(s) and use relevant software for the analysis of data from basic experimental designs.
  • Evaluate the ethical relevance and implications in the design of a questionnaire and in the formulation of its questions.

Assignment 2

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.

 
On successful completion you will be able to:
  • Identify potential issues in survey designs, such as sampling bias and non-sampling errors.
  • Identify suitable experimental designs to solve a variety of problems.
  • Identify appropriate statistical method(s) and use relevant software for the analysis of data from basic experimental designs.

Final Exam

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.

 
On successful completion you will be able to:
  • Apply commonly used survey designs, sampling methods and appropriate statistical technique(s) to estimate population parameters based on a sample from each design.
  • Identify potential issues in survey designs, such as sampling bias and non-sampling errors.
  • Apply basic knowledge to design questionnaires and construct questions.
  • Identify suitable experimental designs to solve a variety of problems.
  • Identify appropriate statistical method(s) and use relevant software for the analysis of data from basic experimental designs.
  • Evaluate the ethical relevance and implications in the design of a questionnaire and in the formulation of its questions.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

Classes

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.

Course materials, recommended text and other references

Lecture notes will be made available on the unit iLearn page (https://iLearn.mq.edu.au/). 

Recommended text:

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.

Technology Used and Required

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.

Unit Schedule

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

8

One-way ANOVA (contd)

 

 Session 2 Break

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)

Policies and Procedures

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.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

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 connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

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.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

The Writing Centre

The Writing Centre provides resources to develop your English language proficiency, academic writing, and communication skills.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via the Service Connect Portal, or contact Service Connect.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/. 

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Changes from Previous Offering

We value student feedback to be able to continually improve the way we offer our units. As such we encourage students to provide constructive feedback via student surveys, to the teaching staff directly, or via the FSE Student Experience & Feedback link in the iLearn page. Student feedback from the previous offering of this unit was very positive overall, with students pleased with the clarity around assessment requirements and the level of support from teaching staff. As such, no change to the delivery of the unit is planned, however we will continue to strive to improve the level of support and the level of student engagement.

Unit information based on version 2024.01R of the Handbook