• Class Number 6471
• Term Code 3370
• Class Info
• Unit Value 6 units
• Topic Intensive Course
• Mode of Delivery In Person
• COURSE CONVENER
• Dr Priya Dev
• LECTURER
• Dr Priya Dev
• Class Dates
• Class Start Date 01/10/2023
• Class End Date 31/12/2023
• Census Date 20/10/2023
• Last Date to Enrol 20/10/2023
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 to analyse financial and investment data;
2. Solve problems using the principles of probability;
3. Recognise and use different statistical distributions;
4. Perform calculations and interpret results of a variety of estimation techniques;
5. Conduct and explain the results of a hypothesis test;
6. Carry out and interpret an analysis of variance test and compare the difference between two or more sets of data; and,
7. 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

No compulsory textbooks. You can choose your preferred introductory to statistics books as an additional resource if you wish.

Statistics for Management & Economics by Gerald Keller is available as an ebook via ANU library and can be found via this link.

## 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 Tuesday 3rd October - Sunday 29th OctoberTopics:
1. Descriptive statistics.
2. Probability.
3. Discrete random variables.
4. Continuous random variables.
5. Sampling distributions.
6. Estimation.
Designed for self study. Read lecture materials and view videos on each topic. Complete tutorial questions on your own or in a study group. Get help via the Discussion Forum or email me and make an appointment.
Online Quiz 1 (15%)
1. Available on Wattle from 9:00am Saturday October 14th to 11:59 pm Saturday October 28.
2. Subject matter of the quiz will be related to lecture material and tutorials already completed.
3. Once commenced, must be completed within 2 hours.
2 Intensive Monday 30th October - Friday 3rd NovemberTopics:7. Hypothesis testing.8. Comparing two populations.9. Analysis of variance10. Chi-squared tests (time permitting)11. Simple linear regression12. Multiple linear regression Online Quiz 2 (15%)Available on Wattle from 9:00am Saturday 4th November to 11:59pm Sunday 12th November.Subject matter of the quiz will be related to lecture material and tutorials already completed.Once commenced, must be completed within 2 hours.
3 Post-intensive Saturday 4th November - Sunday 3rd DecemberSelf study. Review materials and prepare for your Assessment items. Assignment (20%)
1. Released 9:00 am Monday 13th November; Due 11:59pm Monday 20th November.

Final exam (50%)
1. Sunday 3rd December 10am - 3pm.

## Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Online Wattle Quiz 1 15 % 28/10/2023 28/10/2023 1, 2, 3, 4
Online Wattle Quiz 2 15 % 12/11/2023 12/11/2023 1, 2, 3, 4, 5, 6, 7
Assignment 20 % 20/11/2023 30/11/2023 1, 2, 3, 4, 5, 6, 7
Final Exam 50 % 03/12/2023 18/12/2023 1, 2, 3, 4, 5, 6, 7

* 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: 15 %
Due Date: 28/10/2023
Return of Assessment: 28/10/2023
Learning Outcomes: 1, 2, 3, 4

Online Wattle Quiz 1

An online quiz will go live during the 2nd week to complete over the 3rd and 4th week of the pre-intensive period. It will be available to complete over 2 hours from 9:00am Saturday October 14 2023 to 11:59 pm Saturday October 28 2023. On Saturday October 14 a link to the quiz will go live on the class Wattle page. Students will be provided detailed instructions on how to complete the quiz. Further details regarding the grades, number of questions, and subject matter related to the quiz will be outlined along with the link to the quiz. The quiz is to be completed online via the Wattle site and will cover material from Topic 1 (Descriptive Statistics) up to and including Topic 6 (Estimation). You are prohibited from consulting online resources other than class materials available on the class Wattle site. You are also prohibited from discussing the online quiz with anyone.

Value: 15 %
Due Date: 12/11/2023
Return of Assessment: 12/11/2023
Learning Outcomes: 1, 2, 3, 4, 5, 6, 7

Online Wattle Quiz 2

An online quiz will be held during the first post-intensive week. It will be available to complete over 2 hours from 9:00am Saturday November 4 2023 to 11:59 pm Sunday November 12 2023. On Saturday November 4 a link to the quiz will go live on the class Wattle page. Students will be provided detailed instructions on how to complete the quiz. Further details regarding the grades, number of questions, and subject matter of the quiz will be outlined. The quiz is to be completed online via the Wattle site and will cover material from Topic 1 (Descriptive Statistics) up to and including Topic 12 (Multiple Linear Regression). You are prohibited from consulting online resources other than class materials available on the class Wattle site. You are also prohibited from discussing the online quiz with anyone.

Value: 20 %
Due Date: 20/11/2023
Return of Assessment: 30/11/2023
Learning Outcomes: 1, 2, 3, 4, 5, 6, 7

Assignment

An assignment will be released on Monday 13th November 9:00am. Students will be provided detailed instructions on how to complete the assignment on the class Wattle page. 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 by 11:59pm on Monday 20th November 2023. The Assignment will need to be saved or scanned as a PDF file and uploaded via Turnitin. You are prohibited from consulting online resources (other than the class Wattle site) or discussing the assignment with anyone.

Value: 50 %
Due Date: 03/12/2023
Return of Assessment: 18/12/2023
Learning Outcomes: 1, 2, 3, 4, 5, 6, 7

Final Exam

A final exam will be held at the end of the post-intensive period over 5-hours from 10:00am to 3:00pm on Sunday 3rd December 2023. Students will be provided with detailed instructions on how to complete the exam when the exam goes live. It will cover material from the whole course.

The exam will be made available for download via Turnitin on Saturday Dec 3 from 10am AEST. It must be completed on your own and uploaded via Turnitin (as a PDF file) by 3pm on Saturday Dec 3 AEST. You may complete it early. 5 hours gives plenty of time to ask questions, complete the exam, scan it and deal with any IT issues that may arise. You are prohibited from collaborating with ANYONE or utilising resources on the internet to assist you with the Final Exam. You may use the class resources on the class Wattle site only.

## 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.

## Hardcopy Submission

Online submissions via Turnitin only.

## 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

 Dr Priya Dev priya.dev@anu.edu.au

### Research Interests

Applied data analytics: Valuing ESG risks, AI expert systems, distributed ledgers, cryptographic assets, applied probability and statistics for finance. I love designing and commercialising data products. My research interests support this endeavour.

### Dr Priya Dev

 By Appointment By Appointment

## Instructor

 Dr Priya Dev 61250535 priya.dev@anu.edu.au

### Dr Priya Dev

 By Appointment By Appointment