STAT102 Business Data Analysis
150 hours over a twelve-week semester or equivalent study period
Unit rationale, description and aim
This unit provides students with an ethical and practical approach to the analysis of business data uncertainty with emphasis on generating useful information for business and personal decision-making. It covers gathering and describing data, the role of probability in measuring uncertainty, statistical inference using various common parametric and non-parametric techniques and analysis of relationships between variables.
A knowledge of Statistics is critical for many professions including economics, financial analysis, marketing, management and accounting. Numbers and figures are used every day in business to make predictions. If you invest in financial markets, statistics can be used to predict the price of a stock 12 months from now based on company performance measures and other economic factors both locally and globally. This is just one example that illustrates how statistics are used in our modern society. Students will be able to apply data analysis tools with a focus on the application of those tools to understand the issues of vulnerable populations.
The unit provides students with the necessary knowledge and skills needed to apply data analysis techniques for business decision making.
|Learning Outcome Number||Learning Outcome Description|
|LO1||Understand a variety of statistical techniques to datasets and explain the benefits and limitations of these techniques|
|LO2||Use computer-based statistical programs to analyse and interpret financial and non-financial data to inform business decisions|
|LO3||Apply commonly used quantitative methods and techniques to collect and analyse financial and non- financial data|
|LO4||Critically evaluate real-world problems and issues using statistical tools with a focus on vulnerable populations|
Topics will include:
- Role of statistics in decision making, including the focus on vulnerable populations
- Data collection and presentation
- Measuring uncertainty, including probability distributions, normal and other continuous distributions, and sampling distributions
- Inference statistics, including confidence interval estimations, hypothesis testing, analysis of variance
- Forecasting including regression analysis and time series forecasting
- Hypothesis testing including chi-square and non-parametric test, model building, and decision making
- Application of Excel in statistics
Learning and teaching strategy and rationale
The learning and teaching strategy is based on student engagement in the learning process by participation in workshops or equivalent and practical activities designed to reinforce learning. Workshops and equivalent support students to actively participate in the construction and synthesis of knowledge both individually and in small groups. ACU’s teaching policy focuses on learning outcomes for students. Our teaching aims to engage students as active participants in the learning process while acknowledging that all learning must involve a complex interplay of active and receptive processes, constructing meaning for oneself, and learning from others. ACU promotes and facilitates learning that is autonomous and self-motivated, is characterised by the individual taking satisfaction in the mastering of content and skills, and is critical, looking beneath the surface level of information for the meaning and significance of what is being studied.
The workshops or equivalent and practical activities are designed so that students can achieve intended learning outcomes sequentially. Teaching and learning activities will apply the experiential learning model, which encourages students to apply higher-order thinking. The unit ensures that learning activities involve real-world scenarios that in turn, assist with ‘real-world’ preparedness. The unit also uses a scaffolding technique that builds a student’s skills and prepares them for the next phase of the learning process.
This unit is structured with required upfront preparation before workshops or equivalent ; most students report that they spend an average of one hour preparing before the workshops or equivalent and one or more hours after the workshops or equivalent practicing and revising what was covered. The online learning platforms used in this unit provide multiple forms of preparatory and practice opportunities for students to prepare and revise. It is up to individual students to ensure that the out-of-class study is adequate for optimal learning outcomes and successes.
Mode of delivery: This unit is offered in different modes. These are: "Attendance" mode, "Blended" mode and "Online" mode. This unit is offered in three modes to cater to the learning needs and preferences of a range of participants and maximise effective participation for isolated and/or marginalised groups.
In an attendance mode, students will require face-to-face attendance in a specific physical location/s. Students will have face-to-face interactions with lecturer(s) to further their achievement of the learning outcomes. This unit is structured with required upfront preparation before workshops, most students report that they spend an average of one hour preparing before the workshop and one or more hours after the workshop practicing and revising what was covered. The online learning platforms used in this unit provide multiple forms of preparatory and practice opportunities for students to prepare and revise.
In a blended mode, students will require intermittent face-to-face attendance determined by the School. Students will have face-to-face interactions with lecturer(s) to further their achievement of the learning outcomes. This unit is structured with required upfront preparation before workshops. The online learning platforms used in this unit provide multiple forms of preparatory and practice opportunities for students to prepare and revise.
In an online mode, students engage in asynchronous learning and participate in the construction and synthesis of knowledge, while developing their knowledge. Students are required to participate in a series of online interactive activities to enhance their learning including knowledge checks, discussion boards and self paced exercises. This approach allows flexibility for students and facilitates learning and participation for students with a preference for virtual learning.
This unit uses an active learning approach to support students in the exploration of knowledge essential to the discipline. Students are provided with choice and variety in how they learn. Students are encouraged to contribute to asynchronous weekly discussions. Active learning opportunities provide students with opportunities to practice and apply their learning in situations similar to their future professions. Activities encourage students to bring their own examples to demonstrate understanding, application and engage constructively with their peers. Students receive regular and timely feedback on their learning, which includes information on their progress.
Assessment strategy and rationale
In order to pass this unit, students are required to demonstrate mastery of all learning outcomes and achieve an aggregate mark of at least 50%. Marking of each assessment task will be in accordance with rubrics specifically developed to measure student level of achievement of the learning outcomes for each assessment item. Assessments are used primarily to foster learning. ACU adopts a constructivist approach to learning which seeks alignment between the fundamental purpose of each unit, the learning outcomes, teaching and learning strategy, assessment and the learning environment. Using constructive alignment, the assessment tasks are designed for students to demonstrate their achievement of each learning outcome.
The overview of the assessment table is provided below under different delivery modes.
Overview of assessments
Attendance and Blended Mode:
|Brief Description of Kind and Purpose of Assessment Tasks||Weighting||Learning Outcomes|
Assessment Task 1: Open Book Exam
This task requires students to undertake an invigilated examination between Week 5 and 8 of the semester. Students will be provided case study/materials ahead of time with questions on the day.
Submission Type: Individual
Assessment Method: Invigilated examination
Artefact: Written response
Assessment Task 2: The Microsoft Office Certification
This task requires students to attempt the Microsoft Office Expert Certification. Excel Certification demonstrates competency in creating, managing, and distributing spreadsheets for a variety of specialised purposes and situations. The exam covers the ability to customise Excel environments to meet project needs and to enhance productivity. Students will have to take the Excel Certification exam in person or online under the observation of a proctor.
Submission Type: Individual
Assessment Method: Microsoft Certification
Artefact: Microsoft Certification
Assessment Task 3: Case Study
This assessment task consists of a case study where students are provided a real-world scenario and dataset that requires them to apply their statistical skills to support their written arguments, including considering ethical and social (e.g., vulnerable people) perspectives in decision making.
Submission Type: Individual
Assessment Method: Case study
Artefact: Written paper
Representative texts and references
- Almazon, E. P. (2017) An introduction to descriptive & inferential statistics (Available online from ACU Library).
- 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.
- Cooksey, Ray W. "Descriptive Statistics for Summarising Data." In Illustrating Statistical Procedures: Finding Meaning in Quantitative Data, pp. 61-139. Springer, Singapore, 2020.
- Lind, D., Marchal, W., & Wathen, S., 2021, Basic Statistics in Business and Economics 10th Edition, McGraw-Hill, ISBN: 9781260716313
- Smith, P.A. and Lorenc, B., 2020. Robust Official Business Statistics Methodology During COVID-19-related And Other Economic Downturns. Statistical Journal of the International Association for Official Statistics.