• Class Number 9555
• Term Code 3070
• 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 05/10/2020
• Class End Date 04/12/2020
• Census Date 16/10/2020
• Last Date to Enrol 16/10/2020
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 https://library.anu.edu.au/record=b6752644.

## 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 Oct 5 - Oct 30 Topics: Descriptive statistics. Probability. Discrete random variables. Continuous random variables. Sampling distributions. Estimation. Designed for self study. Read lecture materials and view videos on each topic. Follow by completing Tutorial questions on your own or in a study group. Online quiz (10%) Available on Wattle from 9:00am Friday October 23 to 11:59 pm Friday October 30. Once commenced, must be completed within 2 hours.
2 Intensive Nov 02 - Nov 6 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 9 - Dec 4 Self study. Review materials and prepare for your Assessment items. Assignment (30%) Released 9:00 am Friday 20 November; Due 5:00pm Monday 23 November. Final exam (60%) A 5-hour period on Friday Dec 4 (12:00-17:00 AEST).

## Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Online Wattle quiz 10 % 30/10/2020 05/11/2019 1, 2, 3, 4
Assignment 30 % 23/11/2020 30/11/2019 1, 2, 3, 4, 5, 6, 7
Final Exam 60 % 04/12/2020 18/12/2019 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: 10 %
Due Date: 30/10/2020
Return of Assessment: 05/11/2019
Learning Outcomes: 1, 2, 3, 4

Online Wattle quiz

An online quiz will be held during the 4th week of the pre-intensive period. It will be available to complete over 2 hours from 9:00am Friday October 23 to 11:59 pm Friday October 30. Students will be provided detailed instructions on how to complete the quiz on Friday October 23 when the link to the quiz will go live on the class Wattle page. 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 discussing the online quiz with anyone.

Value: 30 %
Due Date: 23/11/2020
Return of Assessment: 30/11/2019
Learning Outcomes: 1, 2, 3, 4, 5, 6, 7

Assignment

An assignment will be released on Friday 20 November by 5:00pm. Students will be provided detailed instructions on how to complete the assignment on Friday 20 November when the link to the assignment will go live 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 5:00pm on Monday 23 November. You will have 3 days over the weekend to complete it. It will need to be either saved or scanned as a PDF file and uploaded via Turnitin. You are prohibited from discussing the assignment with anyone.

Value: 60 %
Due Date: 04/12/2020
Return of Assessment: 18/12/2019
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 on Friday Dec 4 from 12pm to 5pm. Students will be provided with detailed instructions on how to complete the exam by Monday 30 November. It will potentially cover material from the whole course.

Details: The final exam will be held over a 5-hour period on Friday Dec 4 from 12pm to 5pm. The exam will be made available for download via the class Wattle page on Friday Dec 4 from 12pm AEST. It must be completed on your own and uploaded via Turnitin (as a PDF file) by 5pm on Dec 4 AEST. You may complete it early. 5 hours gives plenty of time to complete it, scan it and deal with any IT issues that may arise. You are prohibited from collaborating with anyone.

## 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

Distributed ledgers, cryptographic assets, alternative finance, applied data analytics

### Dr Priya Dev

 By Appointment By Appointment

## Instructor

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

### Dr Priya Dev

 By Appointment By Appointment