Course Title: Data Analysis (AD)

Part A: Course Overview

Course Title: Data Analysis (AD)

Credit Points: 12.00

Important Information:

Please note that this course may have compulsory in-person attendance requirements for some teaching activities.  

To participate in any RMIT course in-person activities or assessment, you will need to comply with RMIT vaccination requirements which are applicable during the duration of the course. This RMIT requirement includes being vaccinated against COVID-19 or holding a valid medical exemption.  

Please read this RMIT Enrolment Procedure as it has important information regarding COVID vaccination and your study at RMIT:  

Please read the Student website for additional requirements of in-person attendance:  


Please check your Canvas course shell closer to when the course starts to see if this course requires mandatory in-person attendance. The delivery method of the course might have to change quickly in response to changes in the local state/national directive regarding in-person course attendance.  


Course Code




Learning Mode

Teaching Period(s)


City Campus


155T Vocational Health and Sciences


Sem 1 2014,
Sem 1 2015,
Sem 1 2016


City Campus


174T School of VE Engineering, Health & Science


Sem 1 2018,
Sem 1 2019,
Sem 1 2020,
Sem 1 2021


City Campus


535T Social Care and Health


Sem 1 2022

Course Coordinator: Rauha Quazi

Course Coordinator Phone: +61 3 9925 4277

Course Coordinator Email:

Course Coordinator Location: 51.7.05

Course Coordinator Availability: by appointment

Pre-requisite Courses and Assumed Knowledge and Capabilities


Course Description

You will learn fundamental mathematical and statistical techniques used by a range of scientists in the laboratory and in the analysis of scientific data.

Objectives/Learning Outcomes/Capability Development

This course contributes to the following Program Learning Outcomes for AD012 Associate Degree in Applied Science:
1. Knowledge Capability: develop an understanding of appropriate and relevant fundamental and applied scientific knowledge with the ability to use and apply that knowledge in a wide range of situations, including new situations within the professional discipline.
3. Problem Solving: apply scientific principles and methods to identify and solve problems associated with a particular area of professional expertise.
4. Teamwork: contribute in a constructive manner to group and team activities and decision making processes

 On completion of this course you should be able to:
1. collect, analyse and report data for research & scientific purposes
2. read and evaluate information and use it to forecast for planning or research purposes
3. use the statistical software package, ‘Minitab’

Overview of Learning Activities

In this course you will learn through the following activities:
• face to face or online teaching: to develop underpinning knowledge about fundamental mathematical and statistical techniques needed in a science laboratory or by scientists
• computer lab sessions using the statistical software package Minitab
• problem solving
• research and report presentation: you will be able to collect, analyse and report data for research purposes. You will also be able to read and evaluate information and use it to forecast for planning or research purposes.

Overview of Learning Resources

All course materials and notes will be available via canvas. You will also have access to the statistical software package, Minitab. A scientific calculator is required to solve mathematical problems. 

Overview of Assessment

Assessment Task 1: Online quizzes
Weighting 20%
This assessment task supports CLOs 1 & 2

Assessment Task 2: Laboratory activities
Weighting 30%
This assessment task supports CLOs 1, 2 & 3

Assessment Task 3: Assignment
Weighting 15%
This assessment task supports CLOs 1, 2 & 3

Assessment Task 4: Final exam 35%