ECON 1008 - Data Analytics I

North Terrace Campus - Semester 2 - 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.

Open All

Course Details

Course Code	ECON 1008
Course	Data Analytics I
Coordinating Unit	Economics
Term	Semester 2
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: Associate Professor Virginie Masson

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 1-hour practical (tutorial) class each week.
Lectures begin in Week 1. Practicals and ASSESSMENT in practicals (tutorial) begin in WEEK 2.

Course Learning Outcomes

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

Apply correctly a variety of statistical techniques, both descriptive and inferential.
Interpret, in plain language, the application and outcomes of statistical techniques.
Interpret computer output and use it to solve problems.
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.

最新糖心Vlog Graduate Attributes

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

最新糖心Vlog 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: 最新糖心Vlog 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 (tutorials).

The lectures provide an overview of the course content and in most cases would provide sufficient material. Students are encouraged to consult the textbook in the instances where they feel they need more practice for specific topics.

Tutors will hold weekly tutorials where they will summarize past weeks lectures and help students with that week's assignments. All assignments will proceed with a lag, i.e. they will be based on the previous weeks lecture materials. Students are encouraged to attend the tutorials to stay on top of the course content

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 and Lecture Material 4 Hours per week

Prepare Quizzes and Assignment Answers 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

o Introduction to Statistics and Analytics
o Analysing Data
o Probability and Chance
o Estimation
o Hypothesis Testing
o Correlation and Regression

Specific Course Requirements

None

The 最新糖心Vlog's policy on Assessment for Coursework Programs is based on the following four principles:

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

Assessment Summary

Assessment Task	Due Date/ Week	Weight	Length(Time)	Learning Outcomes
Quizzes	Weekly	20%	varying	1 - 4
Assignments	Fortnightly	40%	varying	1 - 4
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.
Provided and allowed materials will be announced on MyUni.

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 10 out of 12 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 each of the theme module
Assignments cover primarily the whole of the related module, but may build on material from earlier module.
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

Midterm wriitten test can only be done during the student's Lecture on the date advised on myUni.

Weekly homeworks can only be submitted online, as instructed in tutorials and on myUni. No late assignments 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 .

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 最新糖心Vlog 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 最新糖心Vlog 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
This section contains links to relevant assessment-related policies and guidelines - all university policies.
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 最新糖心Vlog of Adelaide is committed to regular reviews of the courses and programs it offers to students. The 最新糖心Vlog of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.

Authorised by:	Deputy Vice-Chancellor and Vice-President (Academic)
Maintained by:	Course Outlines Administrator

最新糖心Vlog