Semester 2, 2023 Online | |
Units : | 1 |
School or Department : | School of Mathematics, Physics & Computing |
Grading basis : | Graded |
Course fee schedule : | /current-students/administration/fees/fee-schedules |
Staffing
Course Coordinator:
Requisites
Enrolment is not permitted in STA1004 if STA1003 or STA2300 or STA8170 or STA6200 has been previously completed
Overview
Business students can easily access vast quantities of data but need an effective way to analyse, interpret and to translate that date into relevant, timely and meaningful information and, subsequently interpret the outcomes to make more informed and balanced decisions in both a global and domestic business environment. Critical to this translation is the ability to use the tools and techniques of statistical analysis. This course introduces business students to the diversity of business data sources and their applications to gain a better appreciation of the end product of data, i.e., to enhance better business decision-making. We do this by the introduction of relevant statistical techniques. The course provides technical competency in quantitative methods and is a required course as part of CPA and CAANZ accreditation.
The course aims to introduce business students to business data sources and their applications to real world problems faced by businesses. The value of data as well as the reasons why we use appropriate statistically based tools to analyse and apply these statistical techniques forms the foundation of the course. This course deals with the role of statistical analysis for decision-making, the analysis, application and interpretation of data as applied to differing business data sources. Exploration and testing of data as applied to business situations for both parametric and non-parametric situations, understanding the relationship between multiple data sources using regression and correlation analysis and, applications of those techniques in such areas as basic forecasting and application of time series forecasting methods to business situations. Excel spreadsheets are used to better familiarise students with the steps involved in decision making techniques and to enhance the use and interpretation of statistical data likely used in their employment. Problem based learning will form the core teaching approach as well as analysis and thinking.
Course learning outcomes
On successful completion of this course students should be able to:
- Identify, explain and analyse the role of statistics in decision making (TCA08:LO1) (BBCM PO4);
- Analyse and evaluate financial and non-financial data from a variety of sources using appropriate tools to present results in tables and charts as well as numerical descriptive measures for business decision-making purposes (TCA08: LO2, LO3 and LO4; PCA01: LO1) (BBCM PO3 or PO4);
- Communicate clearly, effectively and concisely when presenting and discussing results from the analysis of data (PCA02: LO2) (BBCM PO3);
- Use problem-solving skills, including a selection of parametric and non-parametric tests to analyse, apply and interpret appropriate confidence interval and hypothesis testing procedures for given business data and identify applications to business problems to measure and reduce uncertainty (TCA08: LO3) (BBCM PO1 or PO4);
- Apply thinking skills to solve problems through identifying, making decisions and reaching well-reasoned conclusions applying the relevant regression and correlation coefficients for a data set using Excel and identify ethical issues within a given business situation. (TCA08: LO4; PCA01: LO2, PCA04: LO4) (BBCM PO1 or PO2 or PO4);
- Apply basic regression and time series forecasting tools to business problems and identify ethical issues to social responsibility within the business environment. (CPA/NZ PCA04: LO4) (BBCM PO4).
Topics
Description | Weighting(%) | |
---|---|---|
1. | Introduction to spreadsheets using Excel and its application in statistics and business decision making [TCA Schedule 1 (f)] | 10.00 |
2. | Collect, analyse, and interpret commonly used financial and non-financial business data and present results using pivot tables, charts, and statistics available in Excel [TCA Schedule 1 (a)] | 20.00 |
3. | Introduction to sampling, testing of quantitative business data to make better informed business decisions based on continuous distributions (e.g. the normal distribution) using confidence intervals and hypothesis testing [TCA Schedule 1 (b)&(c)] | 30.00 |
4. | The use and application of regression and correlation in business situations and applying causal effect models such as regression as well as time series forecasting to make business forecasts using Excel templates [TCA Schedule 1 (d)] | 20.00 |
5. | Testing of subjective, interpretative and exploratory business data– collection methods and analysis of non-parametric data including chi-square and non-parametric tests for improved business decision making [TCA Schedule 1 (b) & (e)] | 20.00 |
Text and materials required to be purchased or accessed
Students will need access to Excel (Office 365 or equivalent).
Student workload expectations
To do well in this subject, students are expected to commit approximately 10 hours per week including class contact hours, independent study, and all assessment tasks. If you are undertaking additional activities, which may include placements and residential schools, the weekly workload hours may vary.
Assessment details
Description | Group Assessment |
Weighting (%) | Course learning outcomes |
---|---|---|---|
Quiz 1 | No | 10 | 1,2,3,4 |
Problem Solving | No | 40 | 1,2,3,4,5 |
Quiz 2 | No | 50 | 1,2,3,4,5,6 |