• Class Number 8606
• Term Code 2970
• Class Info
• Unit Value 6 units
• Mode of Delivery In Person
• COURSE CONVENER
• AsPr Hanlin Shang
• LECTURER
• AsPr Hanlin Shang
• Class Dates
• Class Start Date 30/09/2019
• Class End Date 29/11/2019
• Census Date 18/10/2019
• Last Date to Enrol 04/10/2019
SELT Survey Results

Introductory Statistics for Business and Finance (STAT7055)

This course aims to facilitate an understanding of basic statistical techniques used for the analysis of financial and investment data.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

1. Explain and use basic financial statistical techniques and concepts;
2. Use a variety of statistical approaches to analyse financial and investment data;
3. Solve problems using the principles of probability;
4. Recognise and use different statistical distributions;
5. Perform calculations and interpret results of a variety of estimation techniques;
6. Conduct and explain the results of a hypothesis test;
7. Carry out and interpret an analysis of variance test and compare the difference between two or more sets of data;
8. Apply and interpret regression models.

Research-Led Teaching

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.

Required Resources

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 the Hancock library.

Statistics for Management and Economics, 10th Edition, by Gerald Keller.

Staff Feedback

Students will be given feedback in the following forms in this course:

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

1. As a further academic integrity control, students may be selected for a 15 minute individual oral examination of their written assessment submissions.
2. Any student identified, either during the current semester or in retrospect, as having used ghostwriting services will be investigated under the University’s Academic Misconduct Rule.

Class Schedule

Week/Session Summary of Activities Assessment
1 Pre-intensive Sep 30 - Oct 27 Topics: Descriptive statistics. Probability. Discrete random variables. Continuous random variables. Sampling distributions. Estimation. Lecture notes should be viewed. Tutorial questions should be attempted. Online R tutorial should be completed. Online quiz (10%) Available from 9:00am Monday October 21 to 11:50pm Sunday October 27. Once commenced, must be completed within 2 hours.
2 Intensive Oct 28 - Nov 1 Topics: 7. Hypothesis testing. 8. Comparing two populations. 9. Analysis of variance 10. Chi-squared tests (time permitting) 11. Simple linear regression 12. Multiple linear regression
3 Post-intensive Nov 2 - Nov 29 Self study. Assignment (40%) Due 9:00am Monday November 18. Final exam (50%) A 5-hour period on either November 28 or 29.

Tutorial Registration

Please see Wattle for tutors information.

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Online Wattle quiz 10 % 27/10/2019 27/10/2019 1, 2, 3, 4
Assignment 40 % 18/11/2019 22/11/2019 1, 2, 3, 4, 5, 6, 7, 8
Final Exam 50 % 28/11/2019 13/12/2019 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 Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.

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)

See above for examination details.

Value: 10 %
Due Date: 27/10/2019
Return of Assessment: 27/10/2019
Learning Outcomes: 1, 2, 3, 4

Online Wattle quiz

An online quiz will be held during the 4th week of the pre-intensive period. The quiz is to be completed online through the Wattle site and will cover material from Topic 1 (Descriptive Statistics) up to and including Topic 6 (Estimation). It will be available from 9:00am Monday October 21 to 11:50pm Sunday October 27, and once commenced, must be completed within 2 hours.

Value: 40 %
Due Date: 18/11/2019
Return of Assessment: 22/11/2019
Learning Outcomes: 1, 2, 3, 4, 5, 6, 7, 8

Assignment

An assignment will be released on Monday after the intensive teaching period (4 November). The assignment will involve a combination of worked problems to be solved and statistical analysis to be conducted using the R software program and will potentially cover material from the whole course. The assignment will be due at 9:00am on Monday Nov 18. It will need to be either saved or scanned as a PDF file and uploaded to the Wattle site.

Value: 50 %
Due Date: 28/11/2019
Return of Assessment: 13/12/2019
Learning Outcomes: 1, 2, 3, 4, 5, 6, 7, 8

Final Exam

A final exam will be held at the end of the post-intensive period. The final exam is to be accessed and downloaded from the Wattle site and, once completed, will need to be scanned and uploaded back to the Wattle site as a PDF file. It will potentially cover material from the whole course.

Due date: The final exam will be held over a 5-hour period on either November 28 or 29. The timing of the 5-hour period will be decided through consultation with the class. At the beginning of the 5-hour period, the exam will be made available to be downloaded from the Wattle site. It must then be completed and uploaded back to the Wattle site (as a PDF file) within 5 hours.

Online Submission

The ANU uses 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. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

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

Assignments will be returned to students via Wattle.

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.

Resubmission of Assignments

Once submitted, any part of the assessments may not be resubmitted.

Privacy Notice

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

 AsPr Hanlin Shang 61250535 hanlin.shang@anu.edu.au

Research Interests

Functional data analysis; Nonparametric and semiparametric statistics; Bayesian econometrics; Computational statistics; Demographic forecasting; Actuarial studies; Empirical finance; Operations research

AsPr Hanlin Shang

 Wednesday 16:30 18:00 Wednesday 16:30 18:00

Instructor

 AsPr Hanlin Shang 61250535 hanlin.shang@anu.edu.au

AsPr Hanlin Shang

 Wednesday 16:30 18:00 Wednesday 16:30 18:00