Course Title: Data Analysis (AD)

Part A: Course Overview

Course Title: Data Analysis (AD)

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH2210

City Campus

Undergraduate

155T Vocational Health and Sciences

Face-to-Face

Sem 1 2014,
Sem 1 2015,
Sem 1 2016

MATH2210

City Campus

Undergraduate

174T School of VE Engineering, Health & Science

Face-to-Face

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

MATH2210

City Campus

Undergraduate

535T Social Care and Health

Face-to-Face

Sem 1 2022,
Sem 1 2023,
Sem 1 2024

Course Coordinator: Rauha Quazi

Course Coordinator Phone: +61 3 9925 4277

Course Coordinator Email: rauha.quazi@rmit.edu.au

Course Coordinator Location: 51.7.05

Course Coordinator Availability: by appointment


Pre-requisite Courses and Assumed Knowledge and Capabilities

None


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

Weighting 35%

This assessment task supports CLOS 1 and 2