- Class Number 8254
- Term Code 3060
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- Gen Nowak
- Gen Nowak
- Class Dates
- Class Start Date 27/07/2020
- Class End Date 30/10/2020
- Census Date 31/08/2020
- Last Date to Enrol 03/08/2020
This course aims to facilitate an understanding of basic statistical techniques used for the analysis of financial and investment data.
Upon successful completion, students will have the knowledge and skills to:
- Explain and use basic financial statistical techniques and concepts to analyse financial and investment data;
- Solve problems using the principles of probability;
- Recognise and use different statistical distributions;
- Perform calculations and interpret results of a variety of estimation techniques;
- Conduct and explain the results of a hypothesis test;
- Carry out and interpret an analysis of variance test and compare the difference between two or more sets of data; and,
- Apply and interpret regression models.
Statistics provides a way of analysing and understanding data and the variability present in data. Hence statistics is a necessary backbone for almost every area of research. This course will take examples from business, finance and science to introduce fundamental statistical concepts to prepare students for future courses and research projects.
The R statistical software will be used throughout the course. R is freely available for multiple platforms from the Comprehensive R Archive Network (CRAN, https://cran.r-project.org).
There are no formally prescribed textbooks for this course, but the following are some useful recommended textbooks:
- Statistics for Management and Economics, 11th edition, by Gerald Keller.
This textbook closely follows most of the topics covered in the course. The textbook can be purchased from the on-campus bookshop, with the ebook available online through the ANU library.
- Basic Mathematics for Economists, 3rd edition, by Mike Rosser.
For students wanting to brush up on their mathematical skills, chapters 1 to 6 of this textbook cover some assumed background mathematical knowledge. The textbook can be purchased from the on-campus bookshop, with the ebook available online through the ANU library.
- Mathematical Statistics with Applications, 7th edition, by Dennis D. Wackerly, William Mendenhall III and Richard L. Scheaffer.
This textbook is a useful reference for any students who are interested in learning about some of the course topics at a more advanced level. The textbook can be purchased from the on-campus bookshop, with a small number of copies also available for 2-hour loan in the reserve loan section of Hancock library.
All course materials, including lecture materials, lecture videos, tutorial materials, tutorial videos, etc., will be made available on the Wattle site. Students are expected to regularly check the Wattle site for announcements about this course.
Students will be given feedback in the following forms in this course:
- To the whole class during lectures or through Wattle.
- Individually during consultation hours.
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.
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.
To safeguard student privacy, it is university policy that all email communication with students must be through their official ANU email account. Please make sure to use your ANU email account as I will not respond to emails sent from non-ANU email accounts.
|Summary of Activities
|Topic 1: Descriptive statistics. Lecture.
|Topic 2: Probability. Lecture and tutorials.
|Topic 3: Discrete random variables. Lecture and tutorials.
|Topic 4: Continuous random variables. Lecture and tutorials.
|Topic 5: Sampling distributions. Lecture and tutorials.
|First Wattle quiz (week 5 or 6)
|Topic 6: Estimation. Lecture and tutorials.
|First Wattle quiz (week 5 or 6) Mid-semester exam (week 6 or 7)
|Topic 7: Hypothesis testing. Lecture and tutorials.
|Mid-semester exam (week 6 or 7)
|Topic 8: Comparing two populations. Lecture and tutorials.
|Topic 9: ANOVA. Lecture and tutorials.
|Topic 10: Chi-squared tests. Lecture and tutorials.
|Topic 11: Simple linear regression. Lecture and tutorials.
|Topic 12: Multiple linear regression. Lecture and tutorials.
|Second Wattle quiz
Pre-recorded tutorial videos where tutorial questions and solutions are discussed will be made available on a weekly basis. Please see the Wattle site for details on the availability and release time of these videos.
|Return of assessment
|First Wattle Quiz
|Mid Semester Exam
|Second Wattle Quiz
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
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:
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.
Both the mid-semester and final examinations are centrally administered through Examinations, Graduations & Prizes and will be timetabled prior to the examination period. Please check ANU Timetabling for further information. Further information about the examinations will be provided on Wattle closer to the time of the examination.
Assessment Task 1
Learning Outcomes: 1,2,3
First Wattle Quiz
The first optional online Wattle quiz will be held during week 5 or 6 (the due date listed in the Assessment Summary is an indication of the earliest possible date when the quiz may be held). The exact week that the quiz will be held will be determined and announced on Wattle once the mid-semester exam timetable is finalised. It may include material covered in topics 1 to 4, inclusive. Further details regarding the quiz will be provided on Wattle no later than two weeks before the quiz. The first Wattle quiz will be redeemable through the mid-semester exam. That is, if you perform better on the mid-semester exam than on the quiz, the first Wattle quiz will be worth 0% and the mid-semester exam will be worth 35%. Otherwise, the first Wattle quiz will be worth 5% and the mid-semester exam will be worth 30%.
Assessment Task 2
Learning Outcomes: 1,2,3,4
Mid Semester Exam
The mid-semester exam will be held in week 6 or 7 (the due date listed in the Assessment Summary is an indication of the earliest possible date when the exam may be held). It may include material covered in topics 1 to 6, inclusive. Further details regarding the exam will be provided on Wattle no later than two weeks before the exam. The mid-semester exam is not redeemable. Depending on how you perform on the first Wattle quiz, the mid-semester exam will be worth either 30% or 35% (see the details regarding the first Wattle quiz).
Assessment Task 3
Learning Outcomes: 1,2,3,4,5,6,7
Second Wattle Quiz
The second optional online Wattle quiz will be held during week 12 (the due date listed in the Assessment Summary is an indication of the earliest possible date when the quiz may be held). It may include material from the entire semester. Further details regarding the quiz will be provided on Wattle no later than two weeks before the quiz. The second Wattle quiz will be redeemable through the final exam. That is, if you perform better on the final exam than on the quiz, that second Wattle quiz will be worth 0% and the final exam will be worth 65%. Otherwise, the second Wattle quiz will be worth 5% and the final exam will be worth 60%.
Assessment Task 4
Learning Outcomes: 1,2,3,4,5,6,7
The final exam will be held during the university examination period at the end of the semester (the due date listed in the Assessment Summary is an indication of the earliest possible date when the exam may be held). It may include material from the entire semester. Further details regarding the exam will be provided on Wattle no later than teaching week 12 of the semester. Depending on how you perform on the second Wattle quiz, the final exam will be worth either 60% or 65% (see the details regarding the second Wattle quiz).
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.
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.
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.
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.
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.
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.
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
Statistical genetics, spatio-temporal data analysis, penalised regression.