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MATH111 – Quantitative Methods for Science

2017 – S1 Day

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Unit convenor and Lecturer
Rod Yager
Contact via rod.yager@mq.edu.au
Room 617, 12 Wally's Walk
By appointment
Lecturer
David Bulger
Contact via david.bulger@mq.edu.au
Room 530, 12 Wally's Walk
By appointment
Credit points Credit points
3
Prerequisites Prerequisites
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description
This unit provides an introduction to the basic quantitative methods and techniques common to much of Science. In this unit, you will learn how to formulate scientific problems using mathematical and statistical language; be equipped with a range of techniques to analyse and solve these problems, and gain an understanding of how to interpret the solutions obtained. Amongst other topics, this unit will cover rates of change, graphical display and interpretation of data, logarithmic and exponential scales, basic statistical ideas; all in the context of scientific measurement and analysis.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at http://students.mq.edu.au/student_admin/enrolmentguide/academicdates/

Learning Outcomes

  1. Able to demonstrate knowledge of basic principles and concepts of fundamental mathematical and statistical techniques
  2. Apply introductory statistical/mathematical concepts to problems in multiple science disciplines
  3. Identify the mathematical/statistical principles underlying basic discipline-specific problems
  4. Able to model and interpret scientific data at an introductory level
  5. Extract and present qualitative information from a model and/or data set, including the use of graphical methods and appropriate software
  6. Able to present and explain simple examples of the role of mathematics/statistics in multiple science disciplines

General Assessment Information

HURDLES: This unit has no hurdle requirements. This means that there are no second chance examinations and assessments if you happen to fail at your first attempt. Students should aim to get at least 60% for the course work in order to be reasonably confident of passing the unit.

IMPORTANT: If you apply for Disruption to Study for your final examination, you must make yourself available for the week of July 24 – 28, 2017.  If you are not available at that time, there is no guarantee an additional examination time will be offered. Specific examination dates and times will be determined at a later date.

Assessment Tasks

Name Weighting Hurdle Due
Weekly exercises 20% Weekly
Assignment 1 20% Week 8
Assignment 2 20% Week 10
Final Examination 40% Exam period

Weekly exercises

Due: Weekly
Weighting: 20%

Each week's tutorial will include a short quiz on material covered in the previous tutorial.


This Assessment Task relates to the following Learning Outcomes:
  • Able to demonstrate knowledge of basic principles and concepts of fundamental mathematical and statistical techniques
  • Apply introductory statistical/mathematical concepts to problems in multiple science disciplines
  • Identify the mathematical/statistical principles underlying basic discipline-specific problems
  • Able to model and interpret scientific data at an introductory level
  • Extract and present qualitative information from a model and/or data set, including the use of graphical methods and appropriate software
  • Able to present and explain simple examples of the role of mathematics/statistics in multiple science disciplines

Assignment 1

Due: Week 8
Weighting: 20%

Essay relating to the role of mathematics and statistics in various science disciplines.


This Assessment Task relates to the following Learning Outcomes:
  • Able to demonstrate knowledge of basic principles and concepts of fundamental mathematical and statistical techniques
  • Apply introductory statistical/mathematical concepts to problems in multiple science disciplines
  • Identify the mathematical/statistical principles underlying basic discipline-specific problems
  • Able to model and interpret scientific data at an introductory level
  • Extract and present qualitative information from a model and/or data set, including the use of graphical methods and appropriate software
  • Able to present and explain simple examples of the role of mathematics/statistics in multiple science disciplines

Assignment 2

Due: Week 10
Weighting: 20%

Assignment questions providing an opportunity to demonstrate understanding and mastery of the concepts of the unit


This Assessment Task relates to the following Learning Outcomes:
  • Able to demonstrate knowledge of basic principles and concepts of fundamental mathematical and statistical techniques
  • Apply introductory statistical/mathematical concepts to problems in multiple science disciplines
  • Identify the mathematical/statistical principles underlying basic discipline-specific problems
  • Able to model and interpret scientific data at an introductory level
  • Extract and present qualitative information from a model and/or data set, including the use of graphical methods and appropriate software
  • Able to present and explain simple examples of the role of mathematics/statistics in multiple science disciplines

Final Examination

Due: Exam period
Weighting: 40%

2 hour written examination


This Assessment Task relates to the following Learning Outcomes:
  • Able to demonstrate knowledge of basic principles and concepts of fundamental mathematical and statistical techniques
  • Apply introductory statistical/mathematical concepts to problems in multiple science disciplines
  • Identify the mathematical/statistical principles underlying basic discipline-specific problems
  • Able to model and interpret scientific data at an introductory level
  • Extract and present qualitative information from a model and/or data set, including the use of graphical methods and appropriate software
  • Able to present and explain simple examples of the role of mathematics/statistics in multiple science disciplines

Delivery and Resources

  • 3 hours of lectures per week
  • one 2-hour tutorial per week

Unit Schedule

 

WEEK BEGINNING   LECTURE TOPIC TASK DUE
1 27/02/2017   Computation and Measurement in Science  
2 06/03/2017   Predictions and theories in Science  
3 13/03/2017   Displaying data and interpreting graphs in Science  
4 20/03/2017   Oscillations, growth and decay in Science  
5 27/03/2017   Measuring rates of change in Science  
6 03/04/2017   Optimisation in Science  
7 10/04/2017   Accumulation of change in Science  
MID-SESSION BREAK
8 01/05/2017   Predicting outcomes based on theories relating to change in Science A1 
9 08/05/2017   Describing collections of data in Science  
10 15/05/2017   Random variation and chance in Science A2 
11 22/05/2017   Using statistical tests to validate theories in Science  
12 29/05/2017   Transforming data into a mathematical model in Science  
13 05/06/2017 Revision

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central. Students should be aware of the following policies in particular with regard to Learning and Teaching:

Academic Honesty Policy http://mq.edu.au/policy/docs/academic_honesty/policy.html

Assessment Policy http://mq.edu.au/policy/docs/assessment/policy_2016.html

Grade Appeal Policy http://mq.edu.au/policy/docs/gradeappeal/policy.html

Complaint Management Procedure for Students and Members of the Public http://www.mq.edu.au/policy/docs/complaint_management/procedure.html​

Disruption to Studies Policy (in effect until Dec 4th, 2017): http://www.mq.edu.au/policy/docs/disruption_studies/policy.html

Special Consideration Policy (in effect from Dec 4th, 2017): https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policies/special-consideration

In addition, a number of other policies can be found in the Learning and Teaching Category of Policy Central.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/support/student_conduct/

Results

Results shown in iLearn, or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

Learning Skills

Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.

Student Enquiry Service

For all student enquiries, visit Student Connect at ask.mq.edu.au

Equity Support

Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Graduate Capabilities

Discipline Specific Knowledge and Skills

Our graduates will take with them the intellectual development, depth and breadth of knowledge, scholarly understanding, and specific subject content in their chosen fields to make them competent and confident in their subject or profession. They will be able to demonstrate, where relevant, professional technical competence and meet professional standards. They will be able to articulate the structure of knowledge of their discipline, be able to adapt discipline-specific knowledge to novel situations, and be able to contribute from their discipline to inter-disciplinary solutions to problems.

This graduate capability is supported by:

Learning outcomes

  • Able to demonstrate knowledge of basic principles and concepts of fundamental mathematical and statistical techniques
  • Apply introductory statistical/mathematical concepts to problems in multiple science disciplines
  • Identify the mathematical/statistical principles underlying basic discipline-specific problems
  • Able to model and interpret scientific data at an introductory level
  • Extract and present qualitative information from a model and/or data set, including the use of graphical methods and appropriate software
  • Able to present and explain simple examples of the role of mathematics/statistics in multiple science disciplines

Assessment tasks

  • Weekly exercises
  • Assignment 1
  • Assignment 2
  • Final Examination

Problem Solving and Research Capability

Our graduates should be capable of researching; of analysing, and interpreting and assessing data and information in various forms; of drawing connections across fields of knowledge; and they should be able to relate their knowledge to complex situations at work or in the world, in order to diagnose and solve problems. We want them to have the confidence to take the initiative in doing so, within an awareness of their own limitations.

This graduate capability is supported by:

Learning outcomes

  • Able to demonstrate knowledge of basic principles and concepts of fundamental mathematical and statistical techniques
  • Apply introductory statistical/mathematical concepts to problems in multiple science disciplines
  • Identify the mathematical/statistical principles underlying basic discipline-specific problems
  • Able to model and interpret scientific data at an introductory level
  • Extract and present qualitative information from a model and/or data set, including the use of graphical methods and appropriate software
  • Able to present and explain simple examples of the role of mathematics/statistics in multiple science disciplines

Assessment tasks

  • Weekly exercises
  • Assignment 1
  • Assignment 2
  • Final Examination

Effective Communication

We want to develop in our students the ability to communicate and convey their views in forms effective with different audiences. We want our graduates to take with them the capability to read, listen, question, gather and evaluate information resources in a variety of formats, assess, write clearly, speak effectively, and to use visual communication and communication technologies as appropriate.

This graduate capability is supported by:

Learning outcomes

  • Extract and present qualitative information from a model and/or data set, including the use of graphical methods and appropriate software
  • Able to present and explain simple examples of the role of mathematics/statistics in multiple science disciplines

Assessment tasks

  • Weekly exercises
  • Assignment 1
  • Assignment 2
  • Final Examination

Critical, Analytical and Integrative Thinking

We want our graduates to be capable of reasoning, questioning and analysing, and to integrate and synthesise learning and knowledge from a range of sources and environments; to be able to critique constraints, assumptions and limitations; to be able to think independently and systemically in relation to scholarly activity, in the workplace, and in the world. We want them to have a level of scientific and information technology literacy.

This graduate capability is supported by:

Learning outcomes

  • Able to demonstrate knowledge of basic principles and concepts of fundamental mathematical and statistical techniques
  • Apply introductory statistical/mathematical concepts to problems in multiple science disciplines
  • Identify the mathematical/statistical principles underlying basic discipline-specific problems
  • Able to model and interpret scientific data at an introductory level
  • Extract and present qualitative information from a model and/or data set, including the use of graphical methods and appropriate software
  • Able to present and explain simple examples of the role of mathematics/statistics in multiple science disciplines

Assessment tasks

  • Weekly exercises
  • Assignment 1
  • Assignment 2
  • Final Examination

Changes from Previous Offering

Reverted to teaching mathematics and statistics components in separate blocks rather than two lectures on Mathematics and one on Statistics each week as a result of student feedback. 

Changes since First Published

Date Description
28/02/2017 Room numbers have changed again following Department move
17/02/2017 New office numbers have been updated
15/02/2017 Updated office locations following department move