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

Additional Course Costs

The purchase of a scientific calculator.

Examination Material or equipment

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. All exams and quizzes will be open book and all materials are permitted.

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 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 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.

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.

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/

Class Schedule

Week/Session	Summary of Activities	Assessment
1	? Sign up for tutorial via Wattle Topics Chapter 1 - Defining and Collecting Data Chapter 2 - Presenting data in tables and charts Introduction to Microsoft Excel 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)	Weekly Quiz- Chapter 1
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	Weekly Quiz - Chapter 2
3	Topics Chapter 3: Numerical descriptive measures Readings Chapter 3: Sections 3.1 3.2, 3.4, 3.5	Weekly Quiz - Chapter 3
4	Topics Chapter 4 - Basic Probability Readings Chapter 4: All	Weekly Quiz- Chapter 4
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	Weekly Quiz- - Chapter 5
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	Weekly Quiz- - Chapters 6 and 7; Online midsemester will be held either in Week 6 or Week 7
7	Topics Chapter 7 - Sampling distributions Chapter 8 - Confidence interval estimation Readings Chapter 7: Section 7.3 Chapter 8: All	Weekly Quiz - Chapter 8; Online midsemester will be held either in Week 6 or Week 7
8	Topics Chapter 9 - Hypothesis testing : one-sample tests Readings Chapter 9: All	Weekly Quiz - Chapter 9
9	Topics Chapter 10 - Hypothesis testing: two-sample tests Readings Chapter 10: All	Weekly Quiz - Chapter 10
10	Topics Chapter 12 - Simple linear regression Readings Chapter 12: Sections 12.1 - 12.5	Weekly Quiz - Chapter 12 Section 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	Weekly Quiz - Chapter 12: Sections 12.7 - 12.9 and Chapter 13: Sections 13.1 - 13.4; Assignment Due - Wednesday 11:59pm
12	Topics Chapter 13 - Multiple linear regression Readings Chapter 13: Sections 13.6 - 13.7 Review	Online Data analysis assessment (Chapters 1, 2, 3, 7, 8, 9 and 10)

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, prior to the start of the semester. Please note that enrolment in ISIS must be finalised for you to have access to Wattle.

Assessment Summary

Assessment task	Value	Due Date	Return of assessment	Learning Outcomes
Weekly Quizzes	10 %	26/02/2021	21/05/2021	1,2,3,4,5,6,7,8
Mid-Semester Exam	20 %	29/03/2021	07/05/2021	1,2,3,4
Assignment	20 %	19/05/2021	31/05/2021	1,2,3,4,5,6,7,8
Online Data Analysis Task	10 %	24/05/2021	07/06/2021	1,2,3,4,5,6,8
Final Exam	40 %	03/06/2021	01/07/2021	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:

• Student Assessment (Coursework) Policy and Procedure
• Special Assessment Consideration Policy and General Information 
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure

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 ANU Online 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 form of pre-recorded weekly lectures (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.

Assessment Task 1

Weekly Quizzes

There will be 11 short online quizzes held on Wattle testing knowledge and understanding of each week's lecture (and preceding lectures). The quiz will open on Friday at 12am (midnight) at the end of each week (weeks 1-11 inclusive) and close on the following Monday at 11:59pm. That is, the quiz will be open for a 96 hour (4-day) period. Once the quiz is started it will need to be completed in a limited time period. Feedback will be provided by 10am Tuesday following the quiz period. The best 10 quiz marks will count towards this assessment. Each of the best 10 quiz results will contribute 1% towards the final mark for a total of 10%. 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.

Assessment Task 2

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. The mid-semester will cover Chapters 1,2,3 4 and 5 of the textbook. Students will be required to submit working for some questions, as specified in the assessment. All work must be the students' own. Details of the mid-semester 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 mid-semester exam (duration and format) will be made available by the end of Week 4. An online practice exam will be made available on Wattle by the end of Week 4.

The mid-semester exam is not optional and is not redeemable.

Rubric

Assessment Task 3

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 and 9 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 assignments are 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.

The assignment is worth 20% of the overall score in the course and is compulsory.

No late assignments will be accepted without prior permission from the course convenor.

The assignment will be due in Week 11 on Wednesday 19 May by 11:59pm.

Assessment Task 4

Online Data Analysis Task

This assessment requires you to download an Excel data set and question sheet, and answer some applied research questions related to the data set as given to you in the question sheet. This will be an exercise in basic data manipulation, practical application of the statistical tools we have learnt in the course, and effective communication of your results.  Detailed instructions on what to provide in your answer will be given.  A sample data analysis question will be uploaded for you by the end of Week 8. The assessment task will be held in Week 12. Further details on the time limit for the assessment task and other details will be announced closer to the date.

The online data analysis task is worth 10% of the overall score in the course and is compulsory.

 

Assessment Task 5

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

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

Hardcopy submission will not be permitted.

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

Feedback on assignments will be provided online via Turnitin within 12 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

No resubmission of the assignment will be permitted after the due date and time.

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).

• ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
• ANU Diversity and inclusion for students with a disability or ongoing or chronic illness
• ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
• ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
• ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
• ANUSA supports and represents undergraduate and ANU College students
• PARSA supports and represents postgraduate and research students