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Monash University

MAT2003 Continuous mathematics for computer science - Semester 2, 2014

Probability and combinatorics: elementary probability theory, random variables, probability distributions, expected value; counting arguments in combinatorics; statistics. Linear algebra: vectors and matrices, matrix algebra with applications to flow problems and Markov chains; matrix inversion methods. Calculus: differentiation and partial differentiation; constructing Taylor series expansions.

Mode of Delivery

  • Clayton (Day)
  • Malaysia (Day)

Workload Requirements

Minimum total expected workload equals 12 hours per week comprising:

(a.) Contact hours for on-campus students:

  • Three hours of lectures
  • One 1-hour laboratory

(b.) Additional requirements (all students):

  • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

Unit Relationships

Prohibitions

ENG1091, MAT1841, MTH1030

Chief Examiner

Campus Lecturer

Clayton

Daniel McInnes (Daniel.McInnes@monash.edu)

Consultation hours: TBA

Malaysia

Wong Foong Wei (Wong.Foong.Wei@monash.edu)

Consultation hours: TBA

Your feedback to Us

Monash is committed to excellence in education and regularly seeks feedback from students, employers and staff. One of the key formal ways students have to provide feedback is through the Student Evaluation of Teaching and Units (SETU) survey. The University’s student evaluation policy requires that every unit is evaluated each year. Students are strongly encouraged to complete the surveys. The feedback is anonymous and provides the Faculty with evidence of aspects that students are satisfied and areas for improvement.

For more information on Monash’s educational strategy, see:

www.monash.edu.au/about/monash-directions/ and on student evaluations, see: www.policy.monash.edu/policy-bank/academic/education/quality/student-evaluation-policy.html

Previous Student Evaluations of this Unit

Previous feedback has shown satisfaction with this unit, and has not suggested that improvements are needed.

If you wish to view how previous students rated this unit, please go to
https://emuapps.monash.edu.au/unitevaluations/index.jsp

Academic Overview

Learning Outcomes

On successful completion of this unit, students should be able to:
  • apply counting principles in combinatorics and derive key combinatorial identities;
  • describe the principles of elementary probability theory, evaluate conditional probabilities and use Bayes' Theorem;
  • recognise some standard probability density functions, calculate their mean, variance and standard deviation, demonstrate their properties and apply them to relevant problems;
  • implement the principles of experimental design based on those probability density functions, and apply confidence intervals to sample statistics;
  • demonstrate basic knowledge and skills of linear algebra, including to manipulate matrices, solve linear systems, and evaluate and apply determinants;
  • apply knowledge of linear algebra to relevant problems, such as network flow and Markov chains;
  • describe fundamental knowledge of calculus including to differentiate basic, composite, inverse and parametric functions;
  • calculate approximations of functions with tangent lines, evaluate power series and construct Taylor series;
  • perform key skills in the calculus of functions of several variables including to calculate partial derivatives, find tangent planes, identify stationary points and construct Taylor series.

Unit Schedule

Week Activities Assessment
0   No formal assessment or activities are undertaken in week 0
1 COMBINATORICS Selections and arrangements, Pascal's Triangle  
2 Partitions, combinatorial identities, inclusion and exclusion, pigeonhole principle  
3 PROBABILITY Elementary theory, Bayesian analysis, random variables  
4 Mean and standard deviation, binomial distribution, normal distribution, t-distribution  
5 LINEAR ALGEBRA Systems of linear equations, Gaussian elimination Assignment 1 due
6 Homogeneous systems, application to network flow, matrix algebra  
7 Application to Markov Chains  
8 Matrix inverses, determinants, application to coding Assignment 2 due
9 CALCULUS Differentiation  
10 Parametric differation, higher derivatives, power series and Taylor polynomials  
11 Functons of several variables, partial differentiation Assignment 3 due
12 Tangent planes and linear approximations, higher partial derivatives, Taylor polynomial of degree 2 (quadratic appoximation)  
  SWOT VAC No formal assessment is undertaken in SWOT VAC
  Examination period LINK to Assessment Policy: http://policy.monash.edu.au/policy-bank/
academic/education/assessment/
assessment-in-coursework-policy.html

*Unit Schedule details will be maintained and communicated to you via your learning system.

Teaching Approach

Lecture and tutorials or problem classes
This teaching and learning approach provides facilitated learning, practical exploration and peer learning.

Assessment Summary

Examination (3 hours): 70%; In-semester assessment: 30%

Assessment Task Value Due Date
Assignment 1 10% Week 5
Assignment 2 10% Week 8
Assignment 3 10% Week 11
Examination 1 70% To be advised

Assessment Requirements

Assessment Policy

Assessment Tasks

Participation

  • Assessment task 1
    Title:
    Assignment 1
    Description:
    Answer questions on combinatorics, showing all working and clearly showing all steps.
    Weighting:
    10%
    Criteria for assessment:
    • Assignments are judged on correctness of the answers   and
    • Valid calculations and mathematical arguments to obtain those answers.
    Due date:
    Week 5
  • Assessment task 2
    Title:
    Assignment 2
    Description:
    Answer questions on linear algebra, showing all working and clearly showing all steps.
    Weighting:
    10%
    Criteria for assessment:
    • Assignments are judged on correctness of the answers   and
    • Valid calculations and mathematical arguments to obtain those answers.
    Due date:
    Week 8
  • Assessment task 3
    Title:
    Assignment 3
    Description:
    Answer questions on differentiation of functions, showing all working and clearly showing all steps.
    Weighting:
    10%
    Criteria for assessment:
    • Assignments are judged on correctness of the answers   and 
    • Valid calculations and mathematical arguments to obtain those answers.
    Due date:
    Week 11

Examinations

  • Examination 1
    Weighting:
    70%
    Length:
    3 hours
    Type (open/closed book):
    Closed book
    Electronic devices allowed in the exam:
    No calculators or other electronic devices are allowed in the exam. Students will not be disadvantaged by not having a calculator. Where a calculation would be needed, the expression to be evaluated can be written and left without evaluation, and marks will not be reduced for no evaluation.

Learning resources

Monash Library Unit Reading List (if applicable to the unit)
http://readinglists.lib.monash.edu/index.html

Faculty of Information Technology Style Guide

Feedback to you

Examination/other end-of-semester assessment feedback may take the form of feedback classes, provision of sample answers or other group feedback after official results have been published. Please check with your lecturer on the feedback provided and take advantage of this prior to requesting individual consultations with staff. If your unit has an examination, you may request to view your examination script booklet, see http://intranet.monash.edu.au/infotech/resources/students/procedures/request-to-view-exam-scripts.html

Types of feedback you can expect to receive in this unit are:

  • Graded assignments with comments
  • Graded assignments without comments

Extensions and penalties

Returning assignments

Resubmission of assignments

Assignments may not be resubmitted for this unit.

Assignment submission

It is a University requirement (http://www.policy.monash.edu/policy-bank/academic/education/conduct/student-academic-integrity-managing-plagiarism-collusion-procedures.html) for students to submit an assignment coversheet for each assessment item. Faculty Assignment coversheets can be found at http://www.infotech.monash.edu.au/resources/student/forms/. Please check with your Lecturer on the submission method for your assignment coversheet (e.g. attach a file to the online assignment submission, hand-in a hard copy, or use an online quiz). Please note that it is your responsibility to retain copies of your assessments.

Online submission

Electronic submission of assignments is not available for this unit.

Other Information

Policies

Monash has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and to provide advice on how they might uphold them. You can find Monash’s Education Policies at: www.policy.monash.edu.au/policy-bank/academic/education/index.html

Key educational policies include:

Faculty resources and policies

Important student resources including Faculty policies are located at http://intranet.monash.edu.au/infotech/resources/students/

Graduate Attributes Policy

Student Charter

Student services

Monash University Library

Disability Liaison Unit

Students who have a disability or medical condition are welcome to contact the Disability Liaison Unit to discuss academic support services. Disability Liaison Officers (DLOs) visit all Victorian campuses on a regular basis.

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