ECON 1011 - Quantitative Methods for Economic Analysis I

North Terrace Campus - Semester 2 - 2021

This is a course in statistics that focuses on developing analytical techniques and research skills. Enrolment is restricted to the BEc (Adv) students. By the end of the course, students will have an understanding of the complex nature of quantitative research. Students collaborate to set up a real life economic question, collect appropriate data, analyse the data and report on the question. Topics will include sample surveying, regression and correlation analysis, interval estimation and hypothesis testing.

  • General Course Information
    Course Details
    Course Code ECON 1011
    Course Quantitative Methods for Economic Analysis 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 N
    Incompatible ECON 1008; ECON 1008UAC; STATS 1000; STATS 1005
    Restrictions Only available to B.Economics (Advanced) students
    Assessment Typically, reports, test & final exam
    Course Staff

    Course Coordinator: Dr Qazi Haque

    Qazi Haque
    Location: Room 4.47, Nexus 10 Tower
    Telephone: 8313 4927
    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. Apply correctly a variety descriptive and inferential statistical methods.
    2. Interpret, in plan language, the outcomes of statistical methods.
    3. Implement statistical techniques using statistical software and correctly interpret the results.
    4. Apply statistical knowledge in a group based research project; recognise and critically evaluate statistics that are observed in everyday life.
    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)
    Deep discipline knowledge
    • informed and infused by cutting edge research, scaffolded throughout their program of studies
    • acquired from personal interaction with research active educators, from year 1
    • accredited or validated against national or international standards (for relevant programs)
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    Teamwork and communication skills
    • developed from, with, and via the SGDE
    • honed through assessment and practice throughout the program of studies
    • encouraged and valued in all aspects of learning
    3, 4
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    Intercultural and ethical competency
    • adept at operating in other cultures
    • comfortable with different nationalities and social contexts
    • able to determine and contribute to desirable social outcomes
    • demonstrated by study abroad or with an understanding of indigenous knowledges
    Self-awareness and emotional intelligence
    • a capacity for self-reflection and a willingness to engage in self-appraisal
    • open to objective and constructive feedback from supervisors and peers
    • able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
    3, 4
  • Learning Resources
    Required Resources
    There is NO prescribed textbook for this course, though the content will follow closely: Business Statistics, by E. Selvanathan, S. Selvanathan, and G. Keller, 8th Edition. Older versions are OK.

    You may also use Business Statistics, 2015, 3rd(Global) edition by Sharpe, De Veaux, and Velleman. Older versions are also OK.

    There are also web-based resources that covers the key statistical concepts that we will see in class (e.g.

    Students will need a calculator; a basic one that can take squares, square roots would be sufficient. Graphics calculators are allowed but are not necessary.

    Statistical software
    The course will introduce statistical concepts with an emphasis on learning-by-doing using hands-on experience with the use of statistical software, Stata®. This software is available on the workstations in the computer laboratories on campus. You can also access Stata through the ADAPT website either on or off campus using your personal computing device.

    Stata will be used in both lecture and practicals and you are expected to develop familiarity with the software. A good working knowledge of Stata will prepare you for quantitative research in the future. Resources for learning the software will be provided in class.

    Online Learning
    Course materials will be posted on the MyUni course webpage, Extensive use is made of MyUni; please check the announcements regularly.

  • Learning & Teaching Activities
    Learning & Teaching Modes
    This course involves the use of lectures and tutorials.

    Lectures provide an overview of the course content. Students can expect that they will need to study the textbook in order to understand the materials covered.

    The tutorials will involve discussions, solving problem sets, and the use of statistical software (Stata) to address statistical problems.

    Before the tutorials, students will be expected to have attended and understood the lectures and to have read the relevant chapter(s) from the text book.

    This class is only available for face-to-face (on-campus) students.


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

    The workload for this course should consist of:

    Attend lectures 2 hours per week

    Attend tutorials 1 hour per week

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

    The University expects full-time students (i.e. those taking 12 units per semester) to devote a total of 48 hours per week to their studies. This translates to 12 hours per week for a semester course.
    Learning Activities Summary
    Teaching & Learning Activities Teaching & Learning Activities Description Related Learning Outcomes
    Lectures Lectures provide an overview of the course content. Students can expect that they will need to study the textbook in order to comprehend the materials covered. 1-4
    Tutorials Tutorials will involve discussions, solving problem sets, and the use of statistical software (Stata) to address statistical problems. 1-4

    Data types and descriptive statistics

    Randomness, random variables and probability

    Sampling and sampling distributions

    Inference—estimation and hypothesis tests for one proportion and one mean

    Correlation and regression

    Topics in multiple regression

    Time series analysis

    Data management and statistical analysis using Stata

    Specific Course Requirements
    The completion of assignment will require access to Stata. This software is available on the workstations in the computer laboratories on campus. You can also access Stata through the ADAPT website either on or off campus using your personal computing device.
  • 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 Learning Outcomes
    (Best 4 of 6 tests count
    towards final grade) 
    Every fortnight  40% Online multiple choice questions via MyUni 1-3
    Group project Week 12 20% Written report and
    in-class presentation
    Final examination Exam period  40% 2 hours 1-3
    Total 100%
    Assessment Detail

    Quizzes (40%)
    There will be 6 quizzes comprising of multiple choice questions during the semester. The quizzes are administered via MyUni. The best 4 out of 6 quizzes will count for assessment.

    Because not all of quizzes are counted for assessment, no special considerations will be given to students who miss quiz for medical, compassionate, or any other reasons. For any reason, if you attempt less than 4 quizzes, the weight on the final exam will be increased to reflect the shortfall in the quiz components.

    Group project (20% due on the Friday of week 12)
    The project is designed for students to demonstrate that they can apply their knowledge of the statistical tools they have learnt to study a real world economic problem. You are required to work on the project in groups of 4-5 students. More details will be provided at the start of the semester. Students are required to present their group project in class on week 12.

    Final examination (40%)
    There will be a 2 hour final exam. The exam is comprehensive, meaning it can cover all the topics. Statistical tables will be provided.

    Quizzes are administered via MyUni. The report for the group project is to be uploaded and submitted via MyUni (through Turnitin) by 5pm on the Friday of week 12.

    Legible hand-writing and the quality of English expression are considered to be integral parts of the assessment process, and may affect marks. Marks cannot be awarded for answers that cannot be read or understood.
    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.

    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 ( 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’s disciplinary procedures.

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