22803 Quantitative Skills in Accounting and Finance
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particular session, location and mode of offering is the authoritative source
of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.
Subject handbook information prior to 2024 is available in the Archives.
Credit points: 6 cp
Subject level:
Postgraduate
Result type: Grade and marksRequisite(s): 22747 Accounting for Managerial Decisions
These requisites may not apply to students in certain courses.
There are course requisites for this subject. See access conditions.
Description
This subject enables students to develop their ability to collect, analyse and interpret accounting and business data and to use the results of the analysis for decision making. The subject emphasises the development of a practical understanding of various analytical techniques. Students learn how to apply these techniques using statistical tools and to implement the results of their analysis in practical business decisions. These skills and competencies are essential for a future career in accounting and finance in either industry and practice.
Subject learning objectives (SLOs)
| 1. | explain the role of statistical analysis for decision making in accounting and business |
|---|---|
| 2. | identify the sources of accounting and business data and collect data from these sources for analysis |
| 3. | identify and effectively apply commonly used statistical methods and techniques to financial and non-financial data |
| 4. | generate, analyse, and review statistical data including hypothesis testing |
| 5. | effectively interpret, communicate and present the results of quantitative analyses and make relevant predictions to facilitate decision making including the use of charts and tables |
Contribution to the development of graduate attributes
The subject provides students with essential knowledge and skills required in the career of a professional accountant. The subject introduces students to quantitative methods and statistical analysis who have not had any academic research background. It enables students to understand the role that quantitative methods, data collection and analysis could play in business decision making and the importance of ethics and professional integrity in the practice of professional accountants.
The subject contributes to the development of the following Program Learning Objective:
- Apply ethical principles and professional integrity in the context of professional accounting practice (4.2)
Teaching and learning strategies
This subject is taught using a mix of face-to-face teaching, online resources and self-directed study.
Tutorials: In the first part of the class, students are expected to work in groups to solve in-class exercises. Tutorials provide students with the opportunity to review and discuss concepts and receive feedback. Students are expected to contribute and to participate in group discussions and to ask questions. Pre-class preparation is required to solve the in-class problems.
Lectures: The second part of class is dedicated to a lecture. Lectures are designed to introduce the analytical tools which are the focus of the subject and to demonstrate practical examples. Lectures do not cover the course content in-depth but provide an overview of each topic and explain the more difficult concepts using practical examples and demonstration questions. Lecture slides are available prior to class on the course site. Students are expected to add their own additional notes and explanations. It is recommended that students read the relevant textbook chapter/s prior to attending the scheduled lecture on that topic. This background reading is essential to setting the scene for the lecture. This activity will be completed in collaboration with other students and provides students with the opportunity to obtain in-class peer feedback on their learning.
Pre-class preparation: Students are expected to review prior week’s lectures notes, undertake the relevant readings, watch videos and complete the self-study exercises before attending class in order to successfully engage in in-class exercises. The assigned weekly self-study questions and solutions are made available on the learning management system.
Discussion board: Student learning in this subject is also facilitated through online discussion forums which are available throughout session to all students on the learning management system. These discussion forums can be used to ask questions relating to subject content and subject administration. The forums therefore provide an alternative method of obtaining feedback on your learning from subject staff or other students.
Content (topics)
- Sources and collection of accounting data
- Basic descriptive statistics
- Probability and discrete probability distributions
- Normal and continuous distributions
- Confidence interval estimation
- Hypothesis testing
- Regression analysis and forecasting
- Decision analysis and big data analytics
Assessment
Assessment task 1: In-class Quizzes (Individual)*
| Objective(s): | This addresses subject learning objective(s): 1, 3 and 5 |
|---|---|
| Weight: | 20% |
| Length: | Each quiz will run for 40 minutes. |
| Criteria: | This assessment will be graded on the following criteria:
*Note: Late submission of the assessment task will not be marked and awarded a mark of zero. Students who do not complete half of the learning quizzes will have the weighting of that assessment added to the final examination conditional on the students submitting, receiving approval and complying with the requirements of special consideration in accordance with the UTS rules. If the composite mark for the final exam then totals more than 50 per cent and the student is in the final subject of their degree, the UTS rules on borderline result (range of 45-49) shall apply whereby students will be allowed to undertake a supplementary final examination. Where a student completes and passes a supplementary examination, the maximum mark awarded for the subject will be 50 Pass. |
Assessment task 2: Assignment (Group)
| Objective(s): | This addresses subject learning objective(s): 2, 3, 4 and 5 |
|---|---|
| Weight: | 30% |
| Length: | The report is to be a maximum of 15 pages with 1.5 line spacing and 12-point font size, including any tables/figures/charts but excluding the title page, executive summary, references and appendices (excel attachments etc.). Please refer to the assignment brief on Canvas for submission details. |
| Criteria: | This assessment will be graded on the following criteria:
|
Assessment task 3: Final Exam (Individual)
| Intent: | This assessment task is a compulsory component of the subject. A student must attain no less than 40% of the marks in this assessment to pass the subject irrespective of the subject’s total marks. |
|---|---|
| Objective(s): | This addresses subject learning objective(s): 1, 3, 4 and 5 |
| Weight: | 50% |
| Length: | 2 hours |
| Criteria: | This assessment will be graded on the following criteria:
|
Minimum requirements
A student must achieve 50% or more of the subject’s total marks AND achieve 40% or more in the final exam to pass the subject.
A Fail (X) Grade is awarded to a student who attains 50% or more of the overall subject assessment marks but attains less than 40% of the final exam marks. To pass the subject, the student must then attain 50% or more of the marks in the supplementary task, in which case the student is awarded an overall mark of 50P.
Recommended texts
Anderson, D.R., Sweeney, D.J., Williams, T.A., Camm, J.D. and Cochran, J.J., 2020. Modern business statistics with Microsoft Excel. Cengage Learning. 7th Edition. ISBN: 9780357131381.