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ECON 1008 - Data Analytics I

North Terrace Campus - Semester 1 - 2020

In today's world, good decision making relies on data and data analysis. This course helps students develop the understanding that they will need to make informed decisions using data, and to communicate the results effectively. The course is an introduction to the essential concepts, tools and methods of statistics for students in business, economics and similar disciplines, although it may have wider interest. The focus is on concepts, reasoning, interpretation and thinking rather than computation, formulae and theory. Much of the work will require students to write effectively and communicate their ideas with clarity. The course covers two main branches of statistics: descriptive statistics and inferential statistics. Descriptive statistics includes collecting data and summarising and interpreting them through numerical and graphical techniques. Inferential statistics includes selecting and applying the correct statistical technique in order to make estimates or test claims about a population based on a sample. Topics covered may include descriptive statistics, correlation and simple regression, probability, point and interval estimation, hypothesis testing, multiple regression, time series analysis and index numbers. By the end of this course, students should understand and know how to use statistics. Students will also develop some understanding of the limitations of statistical inference and of the ethics of data analysis and statistics. Students will work in small groups in this course; this will develop the skills required to work effectively and inclusively in groups, as in a real work environment. Typically, one component of the assessment requires students to work in teams and collect and analyse data in order to answer a real-world problem of their own choosing.

  • General Course Information
    Course Details
    Course Code ECON 1008
    Course Data Analytics I
    Coordinating Unit Economics
    Term Semester 1
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 3 hours per week. Intensive in Summer Semester.
    Available for Study Abroad and Exchange Y
    Incompatible ECON 1008UAC, ECON 1011, WINEMKTG 1015EX, STATS 1000, STATS 1005, STATS 1004, STATS 1504
    Restrictions Cannot be counted towards BCompSc, BCompGr, BMath, BMath Adv, BMathComp Sci or BEng(Software Engineering) students
    Quota A quota may apply
    Assessment Typically tutorial participation and/or exercises, assignments, tests and final exam
    Course Staff

    Course Coordinator: Dr Terence Cheng

    These are the Course Coordinators for this course for the three semesters of 2020. They will provide further contact details, such as office locations and office hours, at the start of the semester.

    Summer Semester
    Course Coordinator:  Dr Nadezhda Baryshnikova
    Office location:  Nexus 10, Room 4.04
    Contact details: Email nadezhda.baryshnikova@adelaide.edu.au


    Semester 1 
    Course Coordinator: Dr Terence Cheng
    Office Location: Nexus 10, Room 4.10
    Contact details: Email terence.cheng@adelaide.edu.au


    Semester 2
    Course Coordinator:  Dr Ye Han
    Office Location:  
    Contact details: Email ye.han@adelaide.edu.au



    Course Timetable

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

    • Students in this course are expected to attend two 1-hour lectures and one 2-hour practical (tutorial) class each week.
    • PRACTICALS (tutorials) commence in WEEK 2  AND  ASSESSMENT in practicals BEGINS in WEEK 2.
    • ECON 1008UAC 成人大片 College students are asked to read the ECON 1008 Course Outline.
  • Learning Outcomes
    Course Learning Outcomes

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

    1. Apply correctly a variety of statistical techniques, both descriptive and inferential.
    2. Interpret, in plain language, the application and outcomes of statistical techniques.
    3. Interpret computer output and use it to solve problems.
    4. Recognize inappropriate use or interpretation of statistics in other courses, in the media and in life in general and comment critically on the appropriateness of this use of statistics.
    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)
    1-4
    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
    1-4
    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
    1-4
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    1-4
    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
    1-4
    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
    1-4
  • Learning Resources
    Required Resources
    Text book
    Selvanathan S, Selvanathan S and Keller G,  Business Statistics: Australia New Zealand Edition 7
    ISBN 9780170369466


    Calculator
    Students will need a calculator; a basic one that can take squares, square roots etc is sufficient.
    Recommended Resources
    The lecture slides, practical questions and other information will be available for students on Canvas and can be downloaded or printed from there.

    The lecture notes are NOT complete – they indicate what is to be covered in the lecture; you need to attend the lecture and write your own notes.

    In Semester 1, 2 and Summer Semester, it is intended that the lectures be recorded and a recording of each lecture put on Canvas for students who miss a lecture – but be aware that sometimes recordings fail. In that case, a note will be put on MyUni but the lecture may not always be re-recorded and students may need to make other arrangements, such as obtain notes from other students or read the book.

    NOTE: Dictionaries are not allowed in School of Economics exams

    Online Learning
    Extensive use is made of ; please check the announcements regularly. Lecture notes, practical questions, and past exam paper solutions will be made available on MyUni. 

    There is a discussion board on MyUni; this is the preferred way for students to ask questions because this way all students have the same information and any of the staff can reply, allowing for quicker responses.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    This course uses lectures plus practicals.

    The lectures provide an overview of the course content but students must expect that they will need to study the textbook in order to understand the work.

    The tutorials will incorporate team based learning and may include discussion, problem solving activities, individual and group work, student questions and student participation. These practicals provide the opportunity for students to practice; they are vital for success in this course.

    • Before the tutorials, students will be expected to have attended or watched and understood the lectures and to have read the relevant chapter(s) from the text book.
    • During the tutorials,
      • First, students will be asked to record their attendance.
      • There will be time for discussion and questions about the week’s work.
      • Finally, students will be required to work on multiple choice or worked answer questions (homework) in their teams.
    • After the tutorials, students are required to hand in their homework questions online individually. Some of these questions will be marked and returned online. Due dates will be advised on myUni.

    Teams will be formed quickly in the first week of tutorials.
    Workload

    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
    • Study textbook 4 hours per week
    • Prepare homework answer 4 hours per week
    Learning Activities Summary
    Teaching & Learning Activities Related Learning Outcomes
    Lectures (1 hr) 1 - 4
    Tutorials/ practicals (1 x 1 hr) 1 - 4


    The topics to be covered may include 
    • Introduction and data
    • Descriptive statistics
    • Correlation and regression
    • Randomness, random variables and probability
    • Sampling and sampling distributions
    • Inference—estimation and hypothesis tests for one proportion and one mean
    • Inference in regression
    • Topics in multiple regression
    • Time series analysis
    • Index numbers
    Specific Course Requirements
    None.
  • 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
    Due to the current COVID-19 situation modified arrangements have been made to assessments to facilitate remote learning and teaching. Assessment details provided here reflect recent updates.
    Assessment Task Due Date/ Week Weight Length(Word,Time) Learning Outcomes
    Quizzes Weekly 20% Varying 1 - 4
    Assignments Fortnightly 40% Varying 1 - 3
    Final Exam Exam Period 40% 2 hours 1 - 4
    Total 100%
    Assessment Related Requirements
    There are NO hurdle requirements.
    Assessment Detail

    Final exam (40%)

    • This is of 2 hours duration, plus 10 minutes reading time.
    • This exam covers the whole semester.
    • Statistical tables are provided.
    • Please note that, following University policy, dictionaries are not allowed in School of Economics exams.
    • Graphics calculators are allowed but are not required.
    • Legible hand-writing and the quality of English expression are considered to be integral parts of the assessment process. If we can’t read what you have written, we can’t give marks for it.  Students are advised to use a black or blue pen in the exam; write clearly, BEGIN each question ON A NEW PAGE and do not use white out or pencil.
    Quizzes (20%)
    • Quizzes (20%)
    • These are Multiple choice Question quizzes relating to the topics covered in each week.
    • There will be one graded quiz for each week.
    • The mark will be based on the best 8 out of 11 quizzes.
    • Graded quizzes have to be completed before the end of the semester, exact deadline will be announced on MyUni.
      Submission of quizzes will be electronically through MyUni.
    Assignments (40%)
    • There are fortnightly assignments, relating to the topics covered in every two weeks though there can be overlaps in content from previous weeks.
    • Participation in tutorials will contribute to the assignment mark.
    • Submission of assignments will be electronically through MyUni.
    Further details will be provided on MyUni.

    Submission
    Submission of weekly quizzes and the assignments is done online via MyUni.
    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 .

    The policy of the School of Economics is not to return final exam scripts to students. However, they are made available for students to read under the supervision of the Course Coordinator, at a time and place to be announced.
  • 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.

    The revisions to this course, based on student feedback, include a clearer structure of topics, more opportunities to practice questions, a reduction in expenses for online materials and a change in weighting towards continuous assessment.
  • 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.