成人大片

ECON 1010 - Mathematical Economics I

North Terrace Campus - Semester 2 - 2023

This course focuses on the mathematical methods and models that are required to understand current economics and to investigate economic models. Topics may include limits, sequences and series, combinatorics, set theory; univariate and multivariate calculus; matrix algebra and systems of linear equations; and applications in economic models.

  • General Course Information
    Course Details
    Course Code ECON 1010
    Course Mathematical Economics I
    Coordinating Unit Economics
    Term Semester 2
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 4 hours per week
    Available for Study Abroad and Exchange Y
    Incompatible MATHS 1009, MATHS 1010, MATHS 1013, MATHS 1011 and MATHS 1012
    Assumed Knowledge Satisfactory level of achievement in SACE Stage 2 Mathematical Methods, Mathematical Studies, Specialist Mathematics or equivalent
    Restrictions Not suitable for BCompSc, BCompGraphics or BEng(Software Engineering) students
    Assessment Typically exam, test & homework
    Course Staff

    Course Coordinator: Dr Yaping Shan

    Location: Room 3.36, 10 Pulteney Street
    Email: yaping.shan@adelaide.edu.au 

    Course Timetable

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

     
  • Learning Outcomes
    Course Learning Outcomes
    A central aim to this course is to increase "mathematical maturity", confidence and familiarity with the
    types of problems that will be encounted and built upon later.

    On successful completion of this course, students will be able to:

    1. Use appropriate techniques to solve problems with calculus and linear algebra.
    2. Use Matlab at an introductory level.
    3. Model economic questions as mathematical problems.
    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)

    Attribute 1: Deep discipline knowledge and intellectual breadth

    Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.

    1,2,3

    Attribute 2: Creative and critical thinking, and problem solving

    Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.

    1,3

    Attribute 3: Teamwork and communication skills

    Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.

    3

    Attribute 4: Professionalism and leadership readiness

    Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.

    2

    Attribute 8: Self-awareness and emotional intelligence

    Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.

    3
  • Learning Resources
    Required Resources
    Textbook: "Foundations of Mathematical & Computational Economics", Kamran Dadkhah, 2nd edition, Thomson South-Western (Cengage Learning).
    NOTE: The e-book is available from the 成人大片 library.
    Recommended Resources
    Mathematics for Economists.Simon, Carl P and Lawrence Blume. (1994) W.W.Norton

    Note:
    Numerous books with similar topics are available at the 成人大片 library. Choose the book that suits you best. Textbooks aimed at economists are probably best. Be aware that notations may differ.
    Online Learning
    This course uses MyUni intensively to provide you with lectures notes, videos, assignments, etc. You are thus required to check the MyUni website regularly.


  • Learning & Teaching Activities
    Learning & Teaching Modes
    This course is divided into a lecture component and a workshop component. The lecture covers the key concepts of a particular topic to complement the text. Workshops will consolidate your understanding of course material by working through problems similar to those in the lecture.






    Workload

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

    Students in this course are expected to attend all two-hour workshops and all one-hour tutorials. Students are also expected to commit approximately 8 to 10 hours to additional private study. This includes studying the online material provided and preparing the exercises for the workshops and tutorials.
    Learning Activities Summary
    Teaching & Learning Activities Related Learning Outcomes
    Lectures 1
    Workshops 1,3
    Tutorials 1,2


    LECTURE SCHEDULE
    Schedule
    Week 1 Sets, Sets operations, and Functions
    Week 2 Sequences, Series, and Mathematical Proofs
    Week 3 Vectors and Vector Space
    Week 4 Systems of Linear Equations
    Week 5 Matrices and Matrix Algebra
    Week 6 Differentiation: Functions of One Variable - Part 1
    Week 7 Differentiation: Functions of One Variable - Part 2
    Week 8 MidTerm Test (during Workshop time)
    Mid Semester Break
    Week 9 Differentiation: Functions of Several Variables - Part 1
    Week 10 Differentiation: Functions of Several Variables - Part 2
    Week 11 Integration
    Week 12 Review for Final Exam
    Details regarding the learning activities will be available in the weekly study plans on MyUni.
  • 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 Due Date/ Week Weight Length(Word,Time) Learning Outcomes
    Mid-term Test Week 8 20% 1 hour 50 minutes 1
    Weekly assignments Weekly 20% N/A 2
    Matlab assignment Weekly 10% N/A 3
    Final Exam Exam period 50% 3 hours 1
    Total 100%
    Assessment Related Requirements
    1 - Failure to sit the midterm examination will result in receiving zero points. The grade of the final examination will then account for 70% of the overall grade. 

    2 - Only the best 9 out of 10 weekly assignment will count towards you overall average.

    3 - Legible hand-writing and the quality of English expression are considered to be integral parts of the assessment process and may affect marks.
    Assessment Detail
    Mid-semester test  (Week 9)  - 20%
    Date and time: During workshop time, same location. This test will assess the topics of Weeks 1 to 8. It will consist of mathematical problems and short answer questions. NO MATERIAL PERMITTED, i.e. no calculators or books allowed.

    Online Assignments - 20%
    Weekly - You will be asked to submit a number of assignments. Details for the assignments will be provided on MyUni. 

    Matlab Assignment - 10%
    Weekly - You will be asked to use MATLAB to do some exercises from the textbook.                         

    Final Exam - 50%
    There will be a 2-hour exam. The final exam is comprehensive, i.e. it can cover ALL the topics. It will consist of mathematical problems and short answer questions. NO MATERIAL PERMITTED, i.e. no calculators or books allowed.
    Submission
    1 - Extensions and alternative assessment conditions: It is your responsibility to contact the lecturer in the first 2 weeks of the semester to discuss extension or alternative assessment options. This applies to ALL students, included but not limited to those registered with the disability centre or the elite athletes program.

    2 - Weekly assignments MUST be submitted online through MyUni. No other submission type will be accepted.

    3 - Matlab assignments MUST be submitted online through MyUni. No other submission type will be accepted.
    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 .

    Additional Assessment

    If a student receives 45-49 for their final mark for the course they will automatically be granted an additional assessment. This will most likely be in the form of a new exam (Additional Assessment) and will have the same weight as the original exam unless an alternative requirement (for example a hurdle requirement) is stated in this semester’s Course Outline. If, after replacing the original exam mark with the new exam mark, it is calculated that the student has passed the course, they will receive 50 Pass as their final result for the course (no higher) but if the calculation totals less than 50, their grade will be Fail and the higher of the original mark or the mark following the Additional Assessment will be recorded as the final result.
  • 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 (http://www.adelaide.edu.au/policies/101/) 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
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student鈥檚 disciplinary procedures.

The 成人大片 is committed to regular reviews of the courses and programs it offers to students. The 成人大片 therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.