Data and Analysis

• • Subject Introduction Data Types and Statistical Analysis
  • Data Handling, Analysis & Presentation of Data
  • Questions, hypothesis testing and probability
  • Correlation & Linear Regression
  • Content Review
  • The t-test
  • One-way ANOVA
  • Progress Review
  • Presenting Data: Written Reports
  • Experimental Design
  • Presenting Data: Seminars
  • Further Statistical Techniques

No eligibility requirements

Additional requirements

• Other requirements - Weekly online 1 hour tutorial; 3 x half day online workshops per semester. 2 optional Course wide field trips are conducted.

In this subject, you will be introduced to mathematical and statistical methods for analysing scientific, business or technical data to inform and support decision-making. You will explore why data is needed and how it is used to make decisions, including how data are collected, analysed, interpreted and presented, and you will learn and apply a suite of common statistical and mathematical methods to generate evidence for decision-making. You will also be introduced to data management software and learn how to represent and communicate mathematical and statistical information effectively. Through case studies relevant to your discipline, you will learn how to problem solve, generate evidence, and present solutions using data handling and statistical approaches.

This subject also builds on concepts of learning through practice from Year 1 by introducing you to more complex learning experiences including: 

- discipline-based skills and knowledge in dynamic practice situations. This will include authentic and purposeful, industry-related experiences

- concepts of managing effective relationships and communicating with others

- the development and use of adaptive leadership skills and how these skills relate to innovative and entrepreneurial practice 

- the nature of responsible, accountable, and reflective workplace skills, and creative and critical thinking relevant to para-professional practice. 

You will exercise self-awareness, initiative, and judgement to manage yourself and professional relationships effectively. The application of tacit knowledge and capabilities will be reflected in a Practice Manual.

• Exploring Data as Evidence (20%)
• Data Analysis (35%)
• Communicating Data for Decision Making, with Peer Feedback (45%)

For textbook details check your university's handbook, website or learning management system (LMS).