• Class Number 3757
  • Term Code 3230
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
  • COURSE CONVENER
    • Dr Yuan Gao
  • LECTURER
    • Dr Yuan Gao
  • Class Dates
  • Class Start Date 21/02/2022
  • Class End Date 27/05/2022
  • Census Date 31/03/2022
  • Last Date to Enrol 28/02/2022
SELT Survey Results

Quantitative Research Methods provides basic training in the gathering, description and analysis of quantitative information in the social, business, management and financial sciences.

This is a course in basic research methods including discussions of: data gathering issues and techniques; sources of data and potential biases; graphical and numerical data description techniques including simple linear regression, sampling behaviour of averages and the Central Limit Theorem; point and interval estimation procedures; concepts in hypothesis testing for comparing two populations, simple and multiple linear regression; p-values and significance levels.

Learning Outcomes

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

  1. Compare and contrast different sampling methodologies and assess suitability for a range of situations;
  2. Discuss different types of variables and produce appropriate graphical and numerical descriptive statistics;
  3. Explain and apply probability rules and concepts relating to a range discrete and continuous random variables;
  4. Describe the importance of the Central Limit Theorem and its uses and applications;
  5. Use concepts of estimation, including point and interval estimators;
  6. Perform and interpret hypothesis tests for a range of situations;
  7. Perform and interpret simple and multiple linear regressions; and,
  8. Use technology to perform statistical analysis, and interpret statistical software output.

Research-Led Teaching

In order to investigate new fields, make sense of new areas and tackle new problems, we need appropriate tools to explore and summarise data, graphically and numerically, deal with the variation it presents and make decisions under uncertainty. This course will use examples from varied areas to introduce statistical tools, methods and ways of thinking to students and prepare them for future courses, work and research projects. The assignments will also require students to source their own data set for analysis and independently formulate their own research question.

Additional Course Costs

A scientific calculator.

Examination Material or equipment

You will require reliable assess to Wattle and a non-programmable scientific calculator for the duration of the online quizzes and the online exam.

Required Resources

The required textbook is Basic Business Statistics (2019, 5th edition) by Mark L. Berenson, David M. Levine, Kathryn A. Szabat, Martin O'Brien, Nicola Jayne and Judith Watson.


Electronic copies of the textbook are available for a short term loan in the library here: https://library.anu.edu.au/record=b5797359

The e-textbook can be rented from Pearson for 180 days here: https://www.pearson.com.au/9781488664854 . The eBook for purchase and hard copies are also available at this link.

 

This course will also use Microsoft Excel to view data sets, perform some calculations and generate graphs. The software can be accessed for free by ANU students here:

https://services.anu.edu.au/information-technology/software-systems/microsoft-office-365

You will need a scientific calculator to complete the exercises and assessments required for this course.

Staff Feedback

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

  • To the whole class during lectures.
  • Within tutorial groups.
  • Individually during consultation hours.

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

Support for Students

The University offers a number of support services for students. Information on these is available online from http://students.anu.edu.au/studentlife/

Communication via Email

If I, 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. If you have any questions for the teaching and course convenor make sure you email them using your ANU email address. Emails from personal email accounts will not be answered. Announcements

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

Assessment Requirements

Any student identified, either during the current semester or in retrospect, as having used ghost writing services will be investigated under the University’s Academic Misconduct Rule.

Scaling

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, as marks may be scaled. Any scaling applied 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 the scaled mark of that student), and may be either up or down.

Referencing Requirements

In assignments and exams, students must appropriately reference any results, words or ideas that they take from another source which is not their own. A guide can be found at https://academicskills.anu.edu.au/resources/handouts/referencing-basics .

Class Schedule

Week/Session Summary of Activities Assessment
1 ? Sign up for tutorial via Wattle Topics Chapter 1 - Defining and Collecting Data Introduction to Microsoft Excel
2 Topics Chapter 2 - Presenting data in tables and charts Tutorials Begin
3 Topics Chapter 3: Numerical descriptive measures
4 Topics Chapter 4 - Basic Probability Quiz
5 Topics Chapter 5 - Discrete probability distributions Assignment 1 due
6 Topics Chapter 6 - Normal distribution Online midsemester will be held either in W6 or W7
7 Topics Chapter 7 - Sampling distributions Online midsemester will be held either in W6 or W7
8 Topics Chapter 8 - Confidence interval estimation
9 Topics Chapter 9 - Hypothesis testing : one-sample tests
10 Topics Chapter 10 - Hypothesis testing: two-sample tests
11 Topics Chapter 12 - Simple linear regression Assignment 2 due
12 Topics Chapter 13 - Multiple linear regression Review

Tutorial Registration

Tutorials will be available on campus, live through scheduled Zoom sessions and as pre-recorded videos. Information regarding enrolments for these options will be provided on Wattle during O-week of the semester.

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Quiz 5 % 18/03/2022 18/03/2022 1,2,3,4
Assignment 1 10 % 23/03/2022 06/04/2022 1,2,3,4
Mid-Semester Exam 20 % 22/04/2022 06/05/2022 1,2,3,4
Assignment 2 10 % 18/05/2022 30/05/2022 1,2,3,4,5,6,7,8
Final Exam 55 % 02/06/2022 30/06/2022 1,2,3,4,5,6,7,8

* 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 Academic Integrity . 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

Course content delivery will take the form of on-campus lectures (with recordings available via echo360 on Wattle) and weekly tutorials, delivered in hybrid format (on campus, live through scheduled Zoom sessions and as pre-recorded videos). Consultations will be live through Zoom. 

Examination(s)

The mid-semester and final exams will be centrally timetabled by Examinations, Graduations & Prizes prior to the examination period. Please check ANU Timetabling for further information. The exams will be administered online by the lecturer. Any student identified, either during the current semester or in retrospect, as having used ghost writing services will be investigated under the University’s Academic Misconduct Rule.

Assessment Task 1

Value: 5 %
Due Date: 18/03/2022
Return of Assessment: 18/03/2022
Learning Outcomes: 1,2,3,4

Quiz

An online quiz will be held via the Wattle site during Week 4, covering material from Weeks 1–3, inclusive. The quiz will be available from Wednesday to Friday in Week 4. Students have 30 minutes to complete the quiz from when they open the quiz. Feedbacks will be given after the quiz is closed. The students are expected to complete this quiz individually. The quiz is worth 5% of the your overall score and is redeemable towards the final exam. An assessment is redeemable if, when a student performs better in the final exam than in the assessment, then the final exam mark will count instead of the assessment

Assessment Task 2

Value: 10 %
Due Date: 23/03/2022
Return of Assessment: 06/04/2022
Learning Outcomes: 1,2,3,4

Assignment 1

The students are expected to complete this assignment individually. Students will be asked to source a data set of their choice and provide an analysis of their chosen data set using the statistical concepts and methods from Chapters 1, 2, and 3 of the textbook. Detailed instructions will be made available on Wattle by the end of Week 2. The assignments are to be submitted online on Wattle via Turnitin. Assignment 1 is worth 10% of your overall score in the course. The assignment is compulsory and non-redeemable. Once submitted, an assignment cannot be resubmitted. Assignment 1 is due in Week 5. Turnitin is a text-matching software to check for plagiarism. University policies on plagiarism will be strictly enforced. All work must be the student's own.

Assessment Task 3

Value: 20 %
Due Date: 22/04/2022
Return of Assessment: 06/05/2022
Learning Outcomes: 1,2,3,4

Mid-Semester Exam

The mid-semester examination will be held during week 6 or 7 (subject to confirmation from the Examinations Office), covering material from Weeks 1–5 or 1-6, inclusive (depending on when the exam is held). It will be a 2-hour (inc reading and submission time) examination. The exam questions will be posted on Wattle and students are required to submit their written answers through Turnitin. Students will be provided with further details regarding the exam no later than week 4. The mid-term exam is worth 20% of the overall score and is redeemable towards the final exam.

Assessment Task 4

Value: 10 %
Due Date: 18/05/2022
Return of Assessment: 30/05/2022
Learning Outcomes: 1,2,3,4,5,6,7,8

Assignment 2

The students are expected to complete this assignment individually. Students will be required to use their chosen data set to answer questions based on conducting a data analysis. Detailed instructions will be made available on Wattle by the start of Week 9. The assignments are to be submitted online on Wattle via Turnitin. Assignment 2 is worth 10% of your overall score in the course. The assignment is compulsory and non-redeemable. Once submitted, an assignment cannot be resubmitted. Assignment 2 is due in Week 11. Turnitin is a text-matching software to check for plagiarism. University policies on plagiarism will be strictly enforced. All work must be the student's own.

Assessment Task 5

Value: 55 %
Due Date: 02/06/2022
Return of Assessment: 30/06/2022
Learning Outcomes: 1,2,3,4,5,6,7,8

Final Exam

A compulsory final online examination will be held during the university examination period at the end of semester. It is worth 55% of the overall score, or more if other assessment(s) are redeemed. The final examination will cover the entire syllabus. It will be open book and all materials are permitted. All work must be the students' own. The final exam will be held during the exam period with details to be advised no later than Week 10. A practice online exam will be made available on Wattle by the end of Week 12.

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 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.

Hardcopy Submission

There is no hard copy submission.

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

The marked assignments will be returned online.


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

Resubmission is not allowed after the due date.

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).

Dr Yuan Gao
02 612 57290
yuan.gao@anu.edu.au

Research Interests


Functional data analysis; High-dimensional time series.

Dr Yuan Gao

Tuesday 15:00 17:00
Tuesday 15:00 17:00
Dr Yuan Gao
02 612 57290
yuan.gao@anu.edu.au

Research Interests


Dr Yuan Gao

Tuesday 15:00 17:00
Tuesday 15:00 17:00

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