• Class Number 7070
• Term Code 3160
• 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 26/07/2021
• Class End Date 29/10/2021
• Census Date 14/09/2021
• Last Date to Enrol 02/08/2021
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 also require students to source their own data set for analysis and independently formulate their own research question.

A scientific calculator.

## Examination Material or equipment

All assessments will be conducted online. All of these assessments will be open book and all materials are permitted. Some calculations should be completed using a scientific calculator and not other software - this will be specified in the assessment.

## 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

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.

## Class Schedule

Week/Session Summary of Activities Assessment
1 ? Sign up for tutorial via Wattle ? Login to Pearson MyLab Statistics Topics Chapter 1 - Defining and Collecting Data Chapter 2 - Presenting data in tables and charts Introduction to Microsoft Excel and MyLab Statistics Readings Course Outline Chapter 1: Sections 1.1, 1.2 (ignore interval and ratio scales), 1.4, 1.5 Chapter 2: Sections 2.1(Bar Charts)
2 Tutorials Begin Topics Chapter 2 - Presenting data in tables and charts Chapter 3 - Numerical descriptive measures Readings Chapter 2: 2.3 (Frequency Distributions and Histograms) , 2.4, 2.5 Chapter 3: Section 3.1
3 Topics Chapter 3: Numerical descriptive measures Readings Chapter 3: Sections 3.1 3.2, 3.4, 3.5 Self-Practice Questions MyLab Study Plan Chapter 3: Sections 3.1, 3.2, 3.4, 3.5 Quiz1
4 Topics Chapter 4 - Basic Probability Readings Chapter 4: All
5 Topics Chapter 5 - Discrete probability distributions Chapter 6 - Normal distribution Readings Chapter 5: Sections 5.1, 5.2, 5.3 Chapter 6: Sections 6.1, 6.2 Quiz2; Assignmen1 due
6 Topics Chapter 6 - Normal distribution Chapter 7 - Sampling distributions Readings Chapter 6: Sections 6.3, 6.4, 6.6 Chapter 7: Sections 7.1, 7.2 Online midsemester will be held either in W6 or W7
7 Topics Chapter 7 - Sampling distributions Chapter 8 - Confidence interval estimation Readings Chapter 7: Section 7.3 Chapter 8: All Quiz3; Online midsemester will be held either in W6 or W7
8 Topics Chapter 9 - Hypothesis testing : one-sample tests Readings Chapter 9: All
9 Topics Chapter 10 - Hypothesis testing: two-sample tests Readings Chapter 10: All Quiz4
10 Topics Chapter 12 - Simple linear regression Readings Chapter 12: Sections 12.1 - 12.5
11 Topics Chapter 12 - Simple linear regression Chapter 13 - Multiple linear regression Readings Chapter 12: Sections 12.7 - 12.9 Chapter 13: Sections 13.1 - 13.4 Quiz5; Assignment2 due
12 Topics Chapter 13 - Multiple linear regression Readings Chapter 13: Sections 13.6 - 13.7 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
Quizzes 5 % 13/08/2021 29/10/2021 1,2,3,4,5,6,7,8
Assignment 1 10 % 27/08/2021 10/09/2021 1,2,3,4
Mid-Semester Exam 20 % 30/08/2021 01/10/2021 1,2,3,4
Assignment 2 10 % 20/10/2021 02/11/2021 1,2,3,4,5,6,7,8
Final Exam 55 % 04/11/2021 02/12/2020 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).

## 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.

Value: 5 %
Due Date: 13/08/2021
Return of Assessment: 29/10/2021
Learning Outcomes: 1,2,3,4,5,6,7,8

Quizzes

There will be 5 short online quizzes held on Wattle testing knowledge and understanding of the lectures. The quiz will open on Tuesday and close on Sunday of the same week. Once the quiz is started it will need to be completed in a limited time period. Feedback will be provided after the quiz closes. Each of the quiz results will contribute 1% towards the final mark for a total of 5%. More detailed conditions and timing of the quizzes will be announced on Wattle. The quizzes may consist of multiple choice questions or short-answer type questions. All quizzes are open book and all materials are permitted. The quizzes are non-redeemable and are to be completed individually.

Value: 10 %
Due Date: 27/08/2021
Return of Assessment: 10/09/2021
Learning Outcomes: 1,2,3,4

Assignment 1

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.

Both assignments are 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 students' own.

Value: 20 %
Due Date: 30/08/2021
Return of Assessment: 01/10/2021
Learning Outcomes: 1,2,3,4

Mid-Semester Exam

This online exam will be held in Week 6 or Week 7. It will be open book and all materials are permitted. Some calculations should be completed using a scientific calculator and not other software - this will be specified in the assessment. Students will be required to submit working for some questions, as specified in the assessment. All work must be the students' own. Timetabling and other details will be announced closer to the date. The mid-semester exam is redeemable.

Value: 10 %
Due Date: 20/10/2021
Return of Assessment: 02/11/2021
Learning Outcomes: 1,2,3,4,5,6,7,8

Assignment 2

Students will be provided a data set required to answer questions based on 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.

Both assignments are 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 students' own.

Value: 55 %
Due Date: 04/11/2021
Return of Assessment: 02/12/2020
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. The final examination will cover the entire syllabus. It will be open book and all materials are permitted. Students will be required to submit working for some questions, as specified in the assessment. All work must be the students' own. The exam will be centrally timetabled and administered by the lecturer. 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. Further details on the exam (exam duration and format) will be made available by the end of Week 10. A practice online exam will be made available on Wattle by the end of Week 10.

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.

## 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

Due to the impact of Covid-19, all assessment submissions are to be done via Wattle. No hard copy submissions will be accepted.

## Late Submission

Late submission of assessment tasks without an extension will be penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of

assessment tasks is not accepted after 10 days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is

not accepted for take-home examinations.

## 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

Feedback on assignments will be provided online via Turnitin within 14 days after 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

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.
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 2 612 57290 yuan.gao@anu.edu.au

### Research Interests

Functional data analysis; High-dimensional time series.

### Dr Yuan Gao

 Thursday 14:00 16:00 Thursday 14:00 16:00

## Instructor

 Dr Yuan Gao 2 612 57290 yuan.gao@anu.edu.au

### Dr Yuan Gao

 Thursday 14:00 16:00 Thursday 14:00 16:00