• Class Number 6573
• Term Code 3360
• 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 24/07/2023
• Class End Date 27/10/2023
• Census Date 31/08/2023
• Last Date to Enrol 31/07/2023
SELT Survey Results

Quantitative Research Methods (STAT1008)

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 require students to source their own data set for analysis and independently formulate their own research question.

## Examination Material or equipment

The Final exams will be centrally timetabled by Examinations, Graduations & Prizes prior to the examination period. Please check ANU Timetabling for further information.You will require reliable assess to Wattle and a non-programmable scientific calculator for the duration of the quizzes and the 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 RStudio and the R Statistical Environment to view data sets, perform some calculations and generate graphs. This software can be accessed for free here:

https://www.r-project.org/ and https://www.rstudio.com/products/rstudio/ . Further information and support will be provided in week 1.

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). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

## 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

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.

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.

## Class Schedule

Week/Session Summary of Activities Assessment
1 Topics Chapter 1 - Dening and Collecting Data Chapter 2 - Presenting data in tables and charts Introduction to Microsoft Excel
2 Topics Introduction to Microsoft Excel Chapter 3 - Numerical descriptive measures ONLINE QUIZ - Chapters 1 and 2 (Quiz opens 31 July; Quiz closes 6 August)
3 TopicsChapter 3: Numerical descriptive measures Chapter 4 - Basic Probability ONLINE QUIZ - Chapters 3 (Quiz opens 7 August; Quiz closes 13 August)
4 TopicsChapter 4 - Basic Probability Chapter 5 - Discrete probability distributions ONLINE QUIZ - Chapters 3/4 (Quiz opens 14 August; Quiz closes 20 August)
5 TopicsChapter 5 - Discrete probability distributions Chapter 6 - Normal distribution ONLINE QUIZ - Chapters 4/5 (Quiz opens 21 August; Quiz closes 27 August)
6 TopicsChapter 6 - Normal distribution Chapter 7 - Sampling distributions ONLINE QUIZ - Chapters 5/6 (Quiz opens 28 August; Quiz closes 3 September)Mid-semester exam will be held either in W6 or W7
7 TopicsChapter 7 - Sampling distributions Chapter 8 - Condence interval estimation ONLINE QUIZ - Chapters 6/7 (Quiz opens 18 September; Quiz closes 24 September)Mid-semester exam will be held either in W6 or W7
8 TopicsChapter 9 - Hypothesis testing : one-sample tests ONLINE QUIZ - Chapters 7/8 (Quiz opens 25 September; Quiz closes 1 October)
9 TopicsChapter 10 - Hypothesis testing: two-sample tests ONLINE QUIZ - Chapters 9 (Quiz opens 2 October; Quiz closes 8 October)
10 TopicsChapter 12 - Simple linear regression ONLINE QUIZ - Chapters 10 (Quiz opens 9 October; Quiz closes 15 October)
11 TopicsChapter 12 - Simple linear regression Chapter 13 - Multiple linear regression ONLINE QUIZ - Chapters 12 (Quiz opens 16 October; Quiz closes 22 October)Assignment due
12 TopicsChapter 13 - Multiple linear regressionReview

## Tutorial Registration

Tutorials will be held weekly (starting from Week 2). Tutorials will be available on campus. Students should enrol in their tutorial using MyTimetable.

## Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Weekly Quizzes 10 % 06/08/2023 06/08/2023 1,2,3,5,6,7,8
Mid-Semester Exam 20 % 24/09/2023 08/10/2023 1,2,3,4
Assignment 20 % 18/10/2023 01/11/2023 1,2,3,4,5,6,7,8
Final Exam 50 % 03/11/2023 30/11/2023 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 Integrity 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 Skills 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

Course content delivery will take the form of on-campus lectures (with recordings available via echo360 on Wattle) and weekly on-campus tutorials. Participation is strongly encouraged in tutorials.

Attendance at lectures and tutorials, while not compulsory, is expected in line with “Code of Practice for Teaching and Learning”, clause 2 paragraph (b).

## Examination(s)

The final exam will be centrally timetabled by Examinations. Please check ANU Timetabling for further information.

Value: 10 %
Due Date: 06/08/2023
Return of Assessment: 06/08/2023
Learning Outcomes: 1,2,3,5,6,7,8

Weekly Quizzes

There will be 10 short online quizzes held on Wattle testing knowledge and understanding of each week's lecture (and preceding lectures). The quiz will open on Monday at 9 am in each week (weeks 2-11 inclusive) and close on Sunday at 11:59pm. Once the quiz is started it will need to be completed in a limited time period. One attempt per quiz is permitted. Each quiz result will contribute 1% towards the final mark for a total of 10%. The time allowed for each quiz may vary depending on the difficulty of that week's material. The expected time allowed for each quiz is 30 - 60 minutes. Each quiz will consist of up to ten multiple choice questions or short-answer calculation questions. Each question in each quiz will be presented on a separate page and students can navigate backwards and forwards through the quiz. More specific details on the format and duration of each quiz will be announced on Wattle. All quizzes are open book and all materials are permitted. Neither Proctorio nor Zoom will be used for invigilation of the quizzes. Solutions and feedbacks will be released upon the close of each quiz. Therefore, extensions for quizzes are not permitted under any circumstances.

Value: 20 %
Due Date: 24/09/2023
Return of Assessment: 08/10/2023
Learning Outcomes: 1,2,3,4

Mid-Semester Exam

This mid-semester exam will be held in class in Week 6 or Week 7. The mid-semester will cover Chapters 1,2,3 4 and 5 of the textbook. It will be open book and all materials are permitted. The mid-semester exam is worth 20% of the overall score in the course. The mid-semester exam duration will be approximately 1.5 - 2.5 hours. The exam may consist of multiple choice questions, short-answer calculation questions and short-answer written questions. Further details on the mid-semester exam (duration and format) will be made available by the end of Week 4. The mid-semester exam is redeemable.

Value: 20 %
Due Date: 18/10/2023
Return of Assessment: 01/11/2023
Learning Outcomes: 1,2,3,4,5,6,7,8

Assignment

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 , 3 and 7, 8, 9 and 12 of the textbook. Specifically, students will be required to conduct exploratory data analysis on their chosen data set and run statistical hypothesis test(s) to answer research question(s) of their choice based on their chosen data set. Detailed instructions will be made available on Wattle by the end of Week 2. The assignment is to be done individually. The assignment is to be submitted online on Wattle via Turnitin. Turnitin is a text-matching software to check for plagiarism. University policies on plagiarism will be strictly enforced. Late submissions will attract a 5% penalty per day after the deadline unless an extension is granted. Submissions made 10 days after the deadline will not be accepted. The assignment is worth 20% of the overall score in the course and is compulsory. The assignment will be due in Week 11 on Wednesday by 11:59pm. The assignment will be returned by 1 November. Short individual feedback will be provided online along with the grade. Please use the Harvard referencing style https://www.anu.edu.au/students/academic-skills/academic-integrity/referencing/harvard

Value: 50 %
Due Date: 03/11/2023
Return of Assessment: 30/11/2023
Learning Outcomes: 1,2,3,4,5,6,7,8

Final Exam

A compulsory final examination will be held during the university examination period at the end of semester. The exam will be on campus and will cover the entire syllabus. It will be open book and all materials are permitted. The exam will be centrally timetabled. Details of the final examination timetable will be made available on the ANU Timetabling website. The onus is upon students to acquire their own scheduling details. The final exam is worth 50% of the overall score in the course. The exam duration will be approximately 3 - 4 hours. The final exam may consist of multiple choice questions, short-answer calculation questions and short-answer written questions. Students will be required to submit working for some questions, as specified in the assessment. All work must be the students' own. Further details on the exam (exam duration and format) will be made available by the end of Week 10.

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.

The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

## 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

Late submissions will attract a 5% penalty per day after the deadline. Submissions made 10 days after the deadline will not be accepted.

## Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

## 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.

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).

## Convener

 Dr Yuan Gao 61257290

yuan.gao@anu.edu.au

### Research Interests

Functional data analysis; time series forecasting

### Dr Yuan Gao

 Thursday 15:00 16:30 Thursday 15:00 16:30

## Instructor

 Dr Yuan Gao 61257290 yuan.gao@anu.edu.au

### Dr Yuan Gao

 Thursday 15:00 16:30 Thursday 15:00 16:30