BB108 - Business Statistics

Credit Points: 15 credit points

Workload: 36 hours

Prerequisite: N/A

Co-requisite: N/A

Aims & Objectives

This is a first-year core unit offered in the Bachelor of Business program. The unit provides a pathway for students to continue on with a major in Accounting, Marketing or Management. For further information refer to:

This is an introductory level unit which aims to develop the basic quantitative skills needed for solving business related problems. The focus of this unit is to provide students with the knowledge and skills to understand the statistical tools and approaches. In this unit students will identify and apply statistical techniques appropriately to day to day business problems to improve decision making process. It also focuses on providing students with hands on experience to use computer software for statistical analysis.
Unit topics include:

  • Descriptive statistics/Graphical and tabular techniques to present data
  • Measures of central tendency
  • Measures of dispersion
  • Probability and probability distributions
  • Inferential statistics/ Sampling distribution
  • Confidence interval estimation
  • Analysis of variance and chi-squares test
  • Hypothesis testing
  • Correlation and regression analysis

Learning Outcomes

The Course learning outcomes applicable to this unit are listed on the Melbourne Institute of Technology’s website:
At the completion of this unit students should be able to:
a. Understand fundamentals of statistics and its application in business.
b. Assess when and how to use statistical analysis.
c. Solve statistical problems using analytical methods.
d. Generate a range of output from statistical analysis software and interpret the results.
e. Apply knowledge of related statistical analytical techniques as related to business problems.


Assessment Task     Due Date A B Unit Learning Outcomes
1. Formative Assessment Week 3 - 5% a
2. Contribution and Participation Weeks 1-12 - 5% a-e
3. Assignment [Individual] Week 7 20% - a,b,c,e
4. Assignment [Group] Week 10 20% - a-e
5. Case Study Analysis [Individual] (3 hours) TBA - 50% a-e
TOTALS   40% 60%  

Task Type: Type A: unsupervised, Type B: supervised.

Contribution and Participation (5%)

This unit has class participation as an assessment. The assessment task and marking rubric will follow the Guidelines on Assessing Class Participation ( Further details will be provided in the assessment specification on the type of assessment tasks and the marking rubrics.

Teaching Methods

NOTE: All School of Business units 3-hour workshops Flipped Classroom Mode. 

Textbook and Reference Materials

Note: Students are required to purchase the prescribed text book and have it available each week in class.

Prescribed Text Book

  • Anderson, D., Sweeney, D., & Williams, T. (2018). Essentials of Modern Business Statistics with Microsoft Office Excel. (7th ed.). USA: Cengage Learning.

Other recommended references

  • Anderson, D., Sweeney, D., & Williams, T. (2016). Essentials of Modern Business Statistics with Microsoft Office Excel. (6th ed.). USA: Cengage Learning.
  • Selvanathan, E.A., Selvanathan, S., Keller, G. (2016) Business Statistics, ABRIDGED, Ed. 7; Cengage learning.
  • Berenson, M., Levine, D., Szabat, K., O'Brien, M., Watson, J., & Jayne, N., (2015). Basic Business.
  • Statistics. (4th ed.). Australia: Pearson.
  • Larson, R., & Farber, E. (2015). Elementary Statistics: Picturing the World, Global Edition. (6th ed.).
  • England: Pearson.

Journal articles

  • Balakrishnan, N. (2014) Continuous Multivariate Distributions. Wiley StatsRef: Statistics Reference Online, Wiley Online Library, 1-42. 
  • Barr, D. J. (2013) Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of Memory and Language, 68(3), 255-278. 
  • Anderson, M. J., (2008) A new method for non‐parametric multivariate analysis of variance, Austral Ecology:

The Referencing style for this using is APA: See the MIT Library Referencing webpage: and the Unit Moodle page for additional referencing support material and weblinks.

Graduate Attributes

MIT is committed to ensure the course is current, practical and relevant so that graduates are “work ready” and equipped for life-long learning. In order to accomplish this, the MIT Graduate Attributes identify the required knowledge, skills and attributes that prepare students for the industry.
The level to which Graduate Attributes covered in this unit are as follows:

Ability to communicate Independent and Lifelong Learning Ethics Analytical and Problem Solving Cultural and Global Awareness Team work Specialist knowledge of a field of study


Levels of attainment Extent covered
The attribute is covered by theory and practice, and addressed by assessed activities in which the students always play an active role, e.g. workshops, lab submissions, assignments, demonstrations, tests, examinations.
The attribute is covered by theory or practice, and addressed by assessed activities in which the students mostly play an active role, e.g. discussions, reading, intepreting documents, tests, examinations.
The attribute is discussed in theory or practice; it is addressed by assessed activities in which the students may play an active role, e.g. lectures and discussions, reading, interpretation, workshops, presentations.
The attribute is presented as a side issue in theory or practice; it is not specifically assessed, but it is addressed by activities such as lectures or tutorials.
The attribute is not considered, there is no theory or practice or activities associated with this attribute.