• Class Number 6729
• Term Code 3260
• Class Info
• Unit Value 6 units
• Mode of Delivery In Person
• COURSE CONVENER
• Robert Clark
• LECTURER
• Robert Clark
• Class Dates
• Class Start Date 25/07/2022
• Class End Date 28/10/2022
• Census Date 31/08/2022
• Last Date to Enrol 01/08/2022
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.

## 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 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.

Whether you are on campus or studying remotely, there are a variety of online platforms you will use to participate in your study program. These could include videos for lectures and other instruction, two-way video conferencing for interactive learning, email and other messaging tools for communication, interactive web apps for formative and collaborative activities, print and/or photo/scan for handwritten work and drawings, and home-based assessment.

ANU outlines recommended student system requirements to ensure you are able to participate fully in your learning. Other information is also available about the various Learning Platforms you may use.

## 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 Sign up for tutorial using MyTimetable Topics Chapter 1 - Defining and Collecting Data Introduction to the R Statistical Environment
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
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 due
12 Topics Chapter 13 - Multiple linear regression Review

## Tutorial Registration

Tutorials/labs will be available on campus and live through scheduled Zoom sessions. There will not be pre-recorded tutorials. ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage (https://www.anu.edu.au/students/program-administration/timetabling).

## Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Lab Book 10 % 05/08/2022 28/10/2022 1,2,3,5,6,7,8
Quiz 5 % 19/08/2022 19/08/2022 1,2,3,4
Mid-Semester Exam 20 % 23/09/2022 07/10/2022 1,2,3,4
Assignment 20 % 19/10/2022 28/10/2022 1,2,3,4,5,6,7,8
Final Exam 45 % 03/11/2022 01/12/2022 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 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 pre-recorded lectures and on-campus lectures (with recordings available via echo360 on Wattle) and weekly tutorials, delivered in hybrid format (on campus and live through scheduled Zoom sessions). There will not not be pre-recorded tutorials. Participation is strongly encouraged in tutorials/labs, and tutors will be responding to student questions and issues rather than giving a formal presentation. 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.

Value: 10 %
Due Date: 05/08/2022
Return of Assessment: 28/10/2022
Learning Outcomes: 1,2,3,5,6,7,8

Lab Book

Students are required to submit their tutorial/lab working for each of weeks 2-12. Submissions are due at 9pm on the following Monday for each week's lab/tutorial for week 2-11, and are due at 6pm Friday 28 October for the week 12 lab/tutorial. Assessment of this is based on the demonstration of Learning Outcome 8 for the course: Use technology to perform statistical analysis, and interpret statistical software output. Students who attempt each question and submit these attempts on time will be deemed as having met this learning outcome in full, and be awarded full marks for each week (i.e. mark for each week is either 1 or 0), with best 8 marks counting for 10% of the final grade (not redeemable). Note that labs/tutorials will be held live in-person and online, but not prerecorded, and participation in these labs is the best way to get support and advice on use of software and lab/tutorial questions.

Value: 5 %
Due Date: 19/08/2022
Return of Assessment: 19/08/2022
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. Feedback will be given after the quiz is closed via online Wattle quiz mark and solution. The students are expected to complete this quiz individually. The quiz is worth 5% of your overall score and is not redeemable.

Value: 20 %
Due Date: 23/09/2022
Return of Assessment: 07/10/2022
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 will be conducted as an online Wattle quiz. It will not be invigilated but any apparent instances of plagiarism, collusion or other misconduct will be investigated. 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 not redeemable. Feedback will be provided by posting a solution on the Wattle site. Students can also seek individual advice on their performance on the mid semester in consultation sessions.

Value: 20 %
Due Date: 19/10/2022
Return of Assessment: 28/10/2022
Learning Outcomes: 1,2,3,4,5,6,7,8

Assignment

The students are expected to complete this assignment individually. Students will be asked to source a data set of their choice, conduct a data analysis using methods from weeks 1-9 and submit a report. 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. The assignment is worth 20% of your overall score in the course. The assignment is not redeemable. The assignment 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. Feedback will be provided by markup comments on the submission, viewable in Wattle.

Value: 45 %
Due Date: 03/11/2022
Return of Assessment: 01/12/2022
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 45% of the overall score. 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 exam will be conducted as a 3-hour online Wattle quiz. It will not be invigilated but any apparent instances of plagiarism, collusion or other misconduct will be investigated. 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. The exam is not redeemable.

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

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

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.
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

 Robert Clark 0261257292 Robert.Clark@anu.edu.au

### Research Interests

Survey sampling; statistical ecology

### Robert Clark

 Thursday 15:00 17:00 Thursday 15:00 17:00

## Instructor

 Robert Clark 0261257292 robert.clark@anu.edu.au

### Robert Clark

 Thursday 15:00 17:00 Thursday 15:00 17:00