Year

2024

Credit points

10

Campus offering

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  • Term Mode
  • Semester 2Multi-mode
  • Term Mode
  • Semester 2Multi-mode

Prerequisites

Nil

Teaching organisation

150 hours over a twelve-week semester or equivalent study period

Unit rationale, description and aim

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. 

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. Students need to understand the concepts of the data collection methods and presentation, descriptive statistics, inferential statistics, hypothesis testing, analysis of variance, regression analysis, chi-squared testis, and time series forecasting. In addition, students need to apply Excel skills in data analysis. Students need to embrace how data analysis tools can be applied to understand vulnerable populations. The aim of the unit is to help students master the statistical literacy, competency, thinking and reasoning that would be advantageous for potential job settings in a spectrum of disciplines, thus accomplishing the contemporary practical, ethical and global expectations. The unit provides students with the necessary knowledge and data analysis skills needed for a work-ready graduate. 

Learning outcomes

To successfully complete this unit you will be able to demonstrate you have achieved the learning outcomes (LO) detailed in the below table.

Each outcome is informed by a number of graduate capabilities (GC) to ensure your work in this, and every unit, is part of a larger goal of graduating from ACU with the attributes of insight, empathy, imagination and impact.

Explore the graduate capabilities.

Learning Outcome NumberLearning Outcome DescriptionRelevant Graduate Capabilities
LO1Demonstrate a variety of statistical techniques to datasets and explain the benefits and limitations of these techniquesGC1, GC7
LO2Administer computer-based statistical programs to analyse and interpret financial and non-financial data to inform business decisionsGC1, GC10
LO3Implement commonly used quantitative methods and techniques to analyse financial and non- financial dataGC1, GC9
LO4Appraise real-world problems and issues utilising statistical tools with a focus on vulnerable populationsGC1, GC6
LO5Evaluate the nature and limitations of statistical inferences and consequent opinions for the purpose of problem-solving in businessGC1, GC8

Content

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
  • Statistical methods in real life settings

Learning and teaching strategy and rationale

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 workshop's schedule is 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; 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. 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 a range of participants' learning needs and preferences and maximise effective participation for isolated and/or marginalised groups.

Attendance Mode

In a weekly attendance mode, students will require face-to-face attendance in a specific physical location/s. In addition, 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.

Blended Mode

In a blended mode, students will require intermittent face-to-face attendance determined by the School. In addition, 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.

Online Mode

In an online mode, students are given the opportunity to attend facilitated synchronous online seminar classes with other students and participate in the construction and synthesis of knowledge, while developing their knowledge. Students are required to participate in a series of online interactive workshops, which include activities, knowledge checks, discussion and interactive sessions. This approach allows flexibility for students and facilitates learning and participation for students with a preference for virtual learning.

Assessment strategy and rationale

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. In order to pass this unit, students are required to achieve an overall score of at least 50%. Using constructive alignment, the assessment tasks are designed for students to demonstrate their achievement of each learning outcome.

For assessment, students will be required to evaluate data and information from a variety of sources and perspectives through research, integration, and analysis. Students will also need to apply critical thinking skills to identify and solve problems, inform judgments, make decisions, reach well-reasoned conclusions and make recommendations where applicable. Students are expected to communicate clearly and concisely when presenting, discussing, and reporting knowledge and ideas in formal and informal situations.

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 TasksWeightingLearning 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 a case study/materials ahead of time with questions on the day.

Submission Type: Individual

Assessment Method: Invigilated examination

Artefact: Written response

30%

LO1, LO3, LO4

Assessment Task 2: The Microsoft Office Excel Certification

This task requires students to attempt the Microsoft Office: Excel Certification. This Certification covers the fundamentals of creating and managing worksheets and workbooks, creating cells and ranges, creating tables, applying formulas and functions and creating charts and objects.

Submission Type: Individual

Assessment Method: Microsoft Certification

Artefact: Microsoft Certification

30%

LO1, LO2

Assessment Task 3: Case study

This task requires students to draw on and analyse relevant information to demonstrate their knowledge of business data analysis gained throughout the entire semester, including considering ethical perspectives in decision making.

Submission Type: Individual

Assessment Method: Case study

Artefact: Written report

40%

LO2, LO3, LO4, LO5

Representative texts and references

Amrhein, V. et al. (2019) Inferential Statistics as Descriptive Statistics: There Is No Replication Crisis if We Don’t Expect Replication. The American statistician. [Online] 73 (sup1), 262–270.

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

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.

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