Course Title: Math & Stats for Aero, Mech & Auto

Part A: Course Overview

Course Title: Math & Stats for Aero, Mech & Auto

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH2124

City Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

 Sem 1 2006,
Summer2007,
Sem 1 2007,
Sem 2 2007,
Sem 1 2008,
Sem 2 2008,
Sem 1 2009,
Sem 2 2009,
Sem 1 2010,
Sem 2 2010,
Sem 1 2011,
Sem 2 2011,
Sem 1 2012,
Sem 2 2012,
Sem 1 2013,
Sem 2 2013,
Sem 1 2014,
Sem 2 2014,
Sem 1 2015,
Sem 2 2015,
Sem 1 2016,
Sem 2 2016

MATH2124

City Campus

Undergraduate

171H School of Science

Face-to-Face

 Sem 1 2018,
Sem 1 2019,
Sem 2 2019,
Sem 1 2020,
Sem 2 2020

Course Coordinator: Dr Yousong Luo

Course Coordinator Phone: +61 3 9925 2276

Course Coordinator Email: yousong.luo@rmit.edu.au

Course Coordinator Location: 015.04.016

Course Coordinator Availability: By appointment, by email


Pre-requisite Courses and Assumed Knowledge and Capabilities

Required Prior Study

MATH2117 Engineering Mathematics.
MATH2118 Further Engineering Mathematics.
Or equivalent first year university mathematics courses.

Assumed Knowledge

  • Ability to apply the techniques of integral and differential calculus to formulate and solve problems involving change and approximation, including problems with more than one variable.
  • Ability to recognize the properties of the common mathematical functions (polynomials, exponentials and hyperbolic functions, logarithms, inverse trigonometric and inverse hyperbolic functions) and their combinations commonly found in engineering applications.
  • Ability to recognize the properties of vectors and curves in space; apply the techniques of vector analysis to problems involving three-dimensional geometry and motion.
  • Ability to recognize the properties of complex numbers; apply complex numbers to the solution of algebraic equations.
  • Ability to formulate and solve differential equations.
  • Ability to recognize the properties of matrices; apply the techniques of matrix analysis to problems involving three-dimensional geometry and transformations in three-dimensional space; calculate determinants of matrices; find eigenvalues and eigenvectors.
  • Ability to recognize the basic properties of infinite series and apply power series to problems involving approximation of functions.
  • Ability to create a Taylor series approximation to a function of one variable and determine its radius of convergence.

 


Course Description

Mathematics and Statistics for Aerospace, Mechanical and Automotive Engineering is a single semester course consisting of four mathematics topics and some statistics. The course content has been selected, in consultation with the discipline of Aeronautical and Mechanical and Manufacturing Engineering, to provide the necessary mathematical training that will assist and expand your learning experience.


Objectives/Learning Outcomes/Capability Development

This course contributes to the following Program Learning Outcomes for BH070 Bachelor of Engineering (Mechanical Engineering) (Honours); BH074 Bachelor of Engineering (Automotive Engineering) (Honours); BH078 Bachelor of Engineering (Aerospace Engineering) (Honours); BH082 Bachelor of Engineering (Aerospace Engineering) (Honours)/Bachelor of Business (Management); BH084 Bachelor of Engineering (Automotive Engineering) (Honours)/ Bachelor of Business (Management); BH089 Bachelor of Engineering (Mechanical Engineering) (Honours)/ Bachelor of Business (Management); BH090 Bachelor of Engineering (Mechanical Engineering) (Honours)/Bachelor of Science (Biotechnology); BH093 Bachelor of Engineering (Mechanical Engineering) (Honours)/Bachelor of Industrial Design (Honours); BH118 Bachelor of Engineering (Automotive Engineering) (Honours)/ Bachelor of Industrial Design (Honours):

Knowledge and Skill Base:

1.2 Conceptual understanding of mathematics, numerical analysis, statistics, computer and information sciences which underpin the engineering discipline


On successful completion of this course, you would be expected to be able to:

  1. Manipulate Laplace transforms and their inverses, effectively use tables of Laplace transforms and operational formulae and solve appropriate initial value problems.
  2. Apply basic statistical inference techniques, including confidence intervals techniques and hypothesis testing to engineering problems.
  3. Solve non-linear equations using various numerical methods and implement using a computer.
  4. Estimate the solution of systems of ordinary differential equations or high order ordinary differential equations using various numerical methods and implement using a computer.
  5. Manipulate Fourier transforms and their inverses, effectively use tables of Fourier transforms and operational formulae and solve appropriate differential equations using Fourier transforms.
  6. Utilise Multiple Integration in the solution of engineering problems, effectively calculate line integrals, double, triple and surface integrals and apply integral theorems.


Overview of Learning Activities

This course is presented using a mixture of classroom instruction; problem-based tutorial classes; exercises; WebLearn quizzes and tests.

Primarily you will be learning in face-to-face lectures.  An online course site will be used to disseminate course materials, and to provide you access to self-assessment quizzes and tests.

 

WebLearn quizzes are designed to provide instant feedback and can be attempted repeatedly until proficiency in the learning objectives is achieved. You should aim to master each WebLearn quiz before attempting the corresponding WebLearn test. Each test has an associated quiz that opens one week before the test and remains open during the test period. You are given two attempts at each test. Please take notice of the content of the WebLearn bulletin that is displayed each time you go to the WebLearn site. Some WebLearn questions require answers to be entered using a specific syntax. Examples of this syntax are given in the Guide to WebLearn tests, available from the course site. It is your responsibility to master the syntax with the WebLearn quizzes before attempting the corresponding WebLearn test. Answers marked as incorrect, due to syntax errors, will not be remarked.

Weekly homework exercises, with answers, are available to help you obtain proficiency in the course content.

Typical exam style questions are provided to assist in your preparation for the final examination. 


Overview of Learning Resources

The Canvas site links to the Google site where you will find:

  1. Teaching schedule and suggested reading
  2. Assessment guide and assessment schedule.
  3. Guide to WebLearn tests.
  4. Lecture slides.
  5. Recommended references.
  6. Tables and formula sheets.
  7. Weekly exercises and answers.
  8. Practice exam questions
  9. Maple demonstration documents, worksheets and introductory worksheet.
  10. Matlab demonstration  documents and videos.
  11. Mathematica demonstration documents and introductory notebook.
  12. Excell demonstration documents and videos.

        http://rmit.libguides.com/mathstats


Overview of Assessment

 ☒ This course has no hurdle requirements.

 

Assessment Tasks:

 

Assessment Task 1: Weblearn Tests, Weighting 20%, CLOs: 1-6

 

Weeks

Topic/Title

3 

Laplace transforms 

5

Numerical methods

7 

Statistics 

10 

Fourier transforms 

12

Multivariable calculus 

 

Assessment Task 2: Class Tests, Weighting 40%, CLOs: 1-4,6

Weeks

Topic/Title

4

Laplace transforms 

6

Numerical methods 

8 

Statistics 

11 

Multivariable calculus 

 

Assessment Task 3: Final Examination:  Weighting 40%, CLOs: 1-6