• Class Number 7469
• Term Code 2960
• Class Info
• Unit Value 6 units
• Mode of Delivery In Person
• COURSE CONVENER
• Robert Clark
• LECTURER
• Robert Clark
• Class Dates
• Class Start Date 22/07/2019
• Class End Date 25/10/2019
• Census Date 31/08/2019
• Last Date to Enrol 29/07/2019
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 and basic time series; 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; discuss issues with choice of sampling method; sampling vs nonsampling errors; sample vs census choice
2. Discuss different types of variables and produce appropriate graphical and numerical descriptive statistics
3. Understand and apply probability rules and concepts relating to discrete and continuous random variables, including univariate and bivariate distributions and some specific probability density functions, concepts of expectation, variance, correlation and portfolio construction
4. Understand the importance of the Central Limit Theorem and its uses and applications; judging appropriate conditions for its application; use the CLT to find probabilities associated with a range of values for a sample average; sample size determination
5. Consider concepts of estimation — point and interval estimators, unbiasedness and consistency, calculation and interpretation of confidence intervals for a range of situations
6. Perform and interpret hypothesis tests for a range of situations, identifying the situation at hand and assessing whether assumptions are met; discuss types of errors, significance, p-values, make appropriate conclusions with regards to decision making
7. Perform and interpret simple and multiple linear regressions, assessing suitability of the model for the data type and situation; apply and interpret simple time series models
8. Appreciate the use of technology to perform statistical analysis, including interpretation of 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

Permitted materials for the mid semester exam are an English language dictionary, a non- programmable calculator, and one A4 sheet of paper with notes on one side only.

Permitted materials for the final exam are an English language dictionary, a non- programmable calculator, and one A4 sheet of paper with notes on both sides.

For both exams the A4 sheet may be typed, written and/or illustrated as students see fit.

## Required Resources

The 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. The book can be purchased from the on campus bookshop, with a small number of electronic copies also available for loan from the ANU library website. The textbook can also be purchased as an e-book from the publisher (Pearson). This course will also use Microsoft Excel to view data sets, perform some calculations and generate graphs. It is available free on the campus computers. Students will be given access to the Pearson MyLab Statistics digital learning environment associated with the textbook. The MyLab platform provides additional learning resources including study plans and videos to assist students in their learning. Students will be guided to the relevant resources on the platform throughout the course. Students do not need to purchase the textbook to gain access to MyLab Statistics.

## 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 Introduction to Microsoft Excel and MyLab Statistics Readings Course Outline Chapter 1: Sections 1.1, 1.2, 1.4, 1.5 Self-Practice Questions MyLab Study Plan Chapter 1: Sections 1.1, 1.2, 1.4, 1.5
2 Tutorials Begin Topics Chapter 2 - Presenting data in tables and charts Chapter 3 - Numerical descriptive measures Readings Chapter 2: Sections 2.1, 2.3, 2.5, 2.6 Chapter 3: Section 3.1 Self-Practice Questions MyLab Study Plan Chapter 2: Sections 2.1, 2.3, 2.5, 2.6
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
4 Topics Chapter 4 - Basic Probability Readings Chapter 4: All Self-Practice Questions MyLab Study Plan Chapter 4 Online Quiz A (Chapters 1, 2 & 3)
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 Self-Practice Questions MyLab Study Plan Chapter 5: Sections 5.1, 5.2, 5.3 Chapter 6: Sections 6.1, 6.2 Assignment 1 (Chapters 1, 2 & 3)
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 Self-Practice Questions MyLab Study Plan Chapter 6: Sections 6.3, 6.4, 6.6 Mid Semester Exam (proposed) Exact date TBA (Chapters 1, 2, 3, 4)
7 Topics Chapter 7 - Sampling distributions Chapter 8 - Confidence interval estimation Readings Chapter 7: Section 7.3 Chapter 8: All Self-Practice Questions MyLab Study Plan Chapter 7: Section 7.3; Chapter 8
8 Topics Chapter 9 - Hypothesis testing : one-sample tests Readings Chapter 9: All Self-Practice Questions MyLab Study Plan Chapter 9
9 Topics Chapter 10 - Hypothesis testing: two-sample tests Readings Chapter 10: All Self-Practice Questions MyLab Study Plan Chapter 10 Online Quiz B (Chapters 7, 8 and 9)
10 Topics Chapter 12 - Simple linear regression Readings Chapter 12: Sections 12.1 - 12.5 Self-Practice Questions MyLab Study Plan 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 Self-Practice Questions MyLab Study Plan Chapter 12: Sections 12.7 - 12.9 Chapter 13: Sections 13.1 - 13.4 Assignment 2 (Chapters 7, 8, 9 and 10)
12 Topics Chapter 13 - Multiple linear regression Chapter 15 - Chi-Square Tests Readings Chapter 13: Sections 13.6 - 13.7 Chapter 15: Section 15.1 Review Self-Practice Questions MyLab Study Plan Chapter 13: Sections 13.6 - 13.7 Chapter 15: Section 15.1

## Tutorial Registration

Please see Wattle for tutors’ information.

Tutorial signup for this course will be done via the Wattle website. Detailed information about signup times will be provided on Wattle or during your first lecture. When tutorials are available for enrolment, follow these steps:

1.     Log on to Wattle, and go to the course site

2.     Click on the link “Tutorial enrolment”

3.     On the right of the screen, click on the tab “Become Member of…..” for the tutorial class you wish to enter

If you need to change your enrolment, you will be able to do so by clicking on the tab “Leave group….” and then re-enrol in another group. You will not be able to enrol in groups that have reached their maximum number.  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
Online Quiz A 5 % 19/08/2019 26/08/2019 1,2
Assignment 1 5 % 23/08/2019 06/09/2019 1,2,8
Mid Semester Exam 20 % 26/08/2019 19/09/2019 1,2,3,8
Online Quiz B 5 % 08/10/2019 15/10/2019 4,5,6
Assignment 2 5 % 16/10/2019 25/10/2019 4,5,6,8
Final Exam 60 % 31/10/2019 29/11/2019 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 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.

## Examination(s)

Centrally administered examinations through Examinations, Graduations & Prizes will be timetabled prior to the examination period. Please check ANU Timetabling for further information. Exam scripts will not be returned.

Value: 5 %
Due Date: 19/08/2019
Return of Assessment: 26/08/2019
Learning Outcomes: 1,2

Online Quiz A

?                The quizzes are to be attempted online on Wattle.

?                The quizzes are worth 5% each of your overall score in the course.

?                You will have 30 minutes to complete each quiz.

?                Both of the two quizzes are compulsory.

?                Announcements will be made during lectures and on the Wattle course site regarding the availability of the quiz.

Each quiz will consist of five multiple-choice questions.

?                Quiz A will cover: Chapters 1, 2 and 3 of the prescribed textbook and will be held in Week 4.

?                Quiz A will be open to students from 9am Monday 12 August and close at 5pm Monday 19 August.

?                Students will receive their Quiz results online after the quiz closes on 19 August. Solutions will be posted online as well.

Value: 5 %
Due Date: 23/08/2019
Return of Assessment: 06/09/2019
Learning Outcomes: 1,2,8

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.

?                The assignments are to be submitted online on Wattle via Turnitin.

?                The assignments are worth 5% each of your overall score in the course.

?               Both of the two assignments are compulsory.

?                Once submitted, an assignment cannot be resubmitted. No late assignments will be accepted without permission from the course convener.

?                Assignment 1 will be due at the end of Week 5.

?                Announcements will be made during lectures and on the Wattle course site regarding the exact due date and time of the assignments.

?                Turnitin is a text-matching software to check for plagiarism. University policies on plagiarism will be strictly enforced.

## Rubric

Value: 20 %
Due Date: 26/08/2019
Return of Assessment: 19/09/2019
Learning Outcomes: 1,2,3,8

Mid Semester Exam

The mid semester exam will cover Chapters 1, 2, 3 and 4 of the textbook. Centrally administered examinations through Examinations, Graduations & Prizes will be timetabled prior to the examination period. Please check ANU Timetabling for further information. Exam scripts will not be returned. Permitted materials for the midterm exam are an English language dictionary, a non- programmable calculator, and one A4 sheet of paper with notes on one side only.

The A4 sheet can be typed, written and/or illustrated as students see fit.

** The mid semester examination is optional and redeemable.**

Value: 5 %
Due Date: 08/10/2019
Return of Assessment: 15/10/2019
Learning Outcomes: 4,5,6

Online Quiz B

The quizzes are to be attempted online on Wattle.

?                The quizzes are worth 5% each of your overall score in the course.

?                You will have 30 minutes to complete each quiz.

?               Both of the quizzes are compulsory.

?                Announcements will be made during lectures and on the Wattle course site regarding the availability of the quiz.

Each quiz will consist of five multiple-choice questions.

?                Quiz B will cover: Chapters 7, 8 and 9 of the prescribed textbook and will be held in Week 9.

?                Quiz B will be open to students from 9am Tuesday 1 October and close at 5pm Tuesday 8 October.

?                Students will receive their Quiz results online after the quiz closes on 8 October. Solutions will be posted online as well.

Value: 5 %
Due Date: 16/10/2019
Return of Assessment: 25/10/2019
Learning Outcomes: 4,5,6,8

Assignment 2

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 7, 8 and 9 of the textbook. Detailed instructions will be made available on Wattle. The same data set from Assignment 1 may be used.

?                The assignments are to be submitted online on Wattle via Turnitin.

?                The assignments are worth 5% each of your overall score in the course.

?                All two assignments are compulsory.

?                Once submitted, an assignment cannot be resubmitted. No late assignments will be accepted without permission from the course convenor.

?                Assignment 2 will be due on Wednesday 16 October (week 12).

?                Announcements will be made during lectures and on the Wattle course site regarding the exact due date and time of the assignment.

?                Turnitin is a text-matching software to check for plagiarism. University policies on plagiarism will be strictly enforced.

Value: 60 %
Due Date: 31/10/2019
Return of Assessment: 29/11/2019
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 final examination will be 3 hours long and will cover the entire syllabus. Permitted materials for the final exam are an English language dictionary, a non- programmable calculator, and one A4 sheet of paper with notes on both sides. The A4 sheet can be typed, written and/or illustrated as students see fit. Centrally administered examinations through Examinations, Graduations & Prizes will be timetabled prior to the examination period. Please check ANU Timetabling for further information. Exam scripts will not be returned.

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

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

## 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 electronically.

## Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. The Course Convener may grant extensions 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.

## 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 0261003320 robert.clark@anu.edu.au

### Research Interests

Statistical design, survey sampling, multilevel models, statistics in ecology

### Robert Clark

 Tuesday 14:00 16:00 Tuesday 14:00 16:00

## Instructor

 Robert Clark 6125 0487 robert.clark@anu.edu.au

### Robert Clark

 Tuesday 14:00 16:00 Tuesday 14:00 16:00