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