MATHS 1008 - Mathematics for Information Technology I

North Terrace Campus - Semester 2 - 2014

This course provides an introduction to a number of areas of discrete mathematics with wide applicability. Areas of application include: computer logic, analysis of algorithms, telecommunications, gambling and public key cryptography. In addition it introduces a number of fundamental concepts which are useful in Statistics, Computer Science and further studies in Mathematics. Topics covered are: Discrete mathematics: sets, relations, logic, graphs, mathematical induction and difference equations; probability and permutations and combinations; information security and encryption: prime numbers, congruences.

  • General Course Information
    Course Details
    Course Code MATHS 1008
    Course Mathematics for Information Technology I
    Coordinating Unit Mathematical Sciences
    Term Semester 2
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 5 hours per week
    Assumed Knowledge SACE Stage 2 Mathematical Studies
    Assessment ongoing assessment 30%, exam 70%
    Course Staff

    Course Coordinator: Dr Adrian Koerber

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    On successful completion of this course students will be able to:
    1. Demonstrate understanding of concepts in discrete mathematics, probability and cryptography.
    2. Employ methods related to these concepts in a variety of applications.
    3. Apply logical thinking to problem solving in context.
    4. Use appropriate technology to aid problem solving.
    5. Demonstrate skills in writing mathematics.
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)
    Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised. all
    The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 2,3
    An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 1,2,3,4
    A proficiency in the appropriate use of contemporary technologies. 4
    A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life. all
  • Learning Resources
    Required Resources
    Mathematics for Information Technology I student notes.
    Recommended Resources
    1. Ross, K. A. & Wright, C. R. B., Discrete Mathematics, Prentice Hall
    2. Johnsonbaugh, R., Discrete Mathematics (7th ed), Prentice Hall
    3. Goodman, R., An introduction to stochastic models, Benjamin-Cummings
    4. Ross, S., Introduction to probability models (7th ed), Academic Press
    Online Learning
    This course uses MyUni exclusively for providing electronic resources, such as lecture notes, assignment papers, and sample solutions. Students should make appropriate use of these resources. Link to MyUni login page:
  • Learning & Teaching Activities
    Learning & Teaching Modes
    This course relies on lectures to guide students through the material, tutorial classes to provide students with class/small group/individual assistance, and a sequence of written and online assignments to provide formative assessment opportunities for students to practice techniques and develop their understanding of the course.

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    Activity Quantity Workload hours
    Lectures 48 72
    Tutorials 11 22
    Assignments 11 55
    Mid Semester Test 1 7
    Total 156
    Learning Activities Summary
    The two topics of discrete mathematics and probability detailed below are taught in parallel, with two lectures a week on each. The tutorials are a combination of the two topics, pertaining to the previous week's lectures. Note that some sections only loosely fall into the categories of discrete mathematics or probability but are so listed to indicate the stream they are taught in.

    Lecture Outline
    Discrete Mathematics
    • Sets and relations, equivalence relations, functions. (4 lectures)
    • Logic, predicate caclulus. (2 lectures)
    • Types of argument. (2 lectures)
    • Switching circuits. (2 lectures)
    • Graphs, trees, spanning trees, Kruskal's algorithm, binary search trees. (5 lectures)
    • Mathematical induction. (3 lectures)
    • Cryptosysytems, Caesar cipher, Hill cipher. (2 lectures)
    • Elementary number theory. (2 lectures)
    • Public key cryptography, the mathematics of the RSA algorithm. (2 lectures)
    • Sample spaces, events, inclusion-exclusion. (3 lectures)
    • Conditional probablility and the product rule. (1 lecture)
    • Probability trees, independent events, Bayes' Formula, Law of Total Probability. (2 lectures)
    • Discrete random variables and probability distributions. (6 lectures)
    • Counting techniques. (6 lectures)
    • Linear homogeneous recurrence relations with constant coefficients. (6 lectures)
    Tutorial Outline

    Tutorial 1: Sets, relations, Venn diagrams, simple probability.

    Tutorial 2: Functions, 1-1, onto. Conditional probability.

    Tutorial 3: Propositions, truth tables. Probability tree diagrams.

    Tutorial 4: Types of argument, negation. Bayes' Theorem, Law of Total Probability.

    Tutorial 5: Boolean expressions, circuit diagrams. Permutation, combinations, counting arguments.

    Tutorial 6: Mathematical induction, recursive definitions. Partitions. Binomial probability.

    Tutorial 7: Graphs, trees, paths. Binomial proability distribution.

    Tutorial 8: Kruskal's algorithm. Binary search trees. Mode, median. Normal distribution.

    Tutorial 9: Binary search trees. Caesar cipher. Markov chains.

    Tutorial 10: Hill cipher, elementary number theory. Recurrence relations.

    Tutorial 11: Congruence, Fermat's theorem. Inhomogeneous recurrence relations.

    Note: Precise tutorial content may vary due to the vagaries of public holidays.

  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Task Type Weighting Learning Outcomes
    Assignments Formative 15% all
    Mid Semester Test Summative and Formative 15% 1,2,3
    Exam Summative 70% 1,2,3,5
    Assessment Related Requirements
    An aggregate score of 50% is required to pass the course. Furthermore students must achieve at least 45% on the final examination to pass the course.
    Assessment Detail
    Assessment itemDistributedDue dateWeighting
    Assignment 1 week 1 week 3 1.4%
    Assignment 2 week 2 week 4 1.4%
    Assignment 3 week 3 week 5 1.4%
    Assignment 4 week 4 week 6 1.4%
    Assignment 5 week 5 week 7 1.4%
    Assignment 6 week 6 week 8 1.4%
    Assignment 7 week 7 week 9 1.4%
    Assignment 8 week 8 week 10 1.4%
    Assignment 9 week 9 week 11 1.4%
    Assignment 10 week 10 week 12 1.4%
    Assignment 11 week 11 week 13 1.4%
    Mid Semester Test week 8 15%
    1. All written assignments are to be submitted at the designated time and place with a signed cover sheet attached.
    2. Late assignments will not be accepted without a medical certificate.
    3. Written assignments will have a one week turn-around time for feedback to students.
    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy ( course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
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