## ECON 1011 - Quantitative Methods for Economic Analysis I

### North Terrace Campus - Semester 2 - 2020

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 Quantitative Methods for Economic Analysis I School of Economics Semester 2 Undergraduate North Terrace Campus 3 Up to 4 hours per week N ECON 1008; STATS 1000; STATS 1005 Only available to B.Economics (Advanced) students 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.
##### Course Staff

Course Coordinator: Dr Terence Cheng

Terence Cheng
Location: Room 4.06, Nexus 10 Tower
Telephone: 8313 1175
##### 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. Describe and apply a variety of graphical and numerical descriptive statistics.
2. Describe and apply concepts of randomness and probability, probability rules, probability models, and construct measures of random variation.
3. Identify the concepts of samples, sampling distributions, and estimation; evaluate the properties of point and interval estimators; construct and interpret confidence intervals.
4. Construct and interpret simple and multiple linear regression models; perform and interpret hypothesis tests; draw appropriate conclusions from models and tests to inform discussion making.
5. Perform statistical techniques using statistical software; analyse and interpret the results.
6. Apply statistical knowledge in other courses; recognise and critically evaluate statistics that are observed in everyday life.

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)
1-6
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
1-6
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
1-6
• technology savvy
• professional and, where relevant, fully accredited
• forward thinking and well informed
• tested and validated by work based experiences
1-6
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
1-6
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
1-6
• Learning Resources
##### Required Resources
Textbook
There is NO prescribed textbook for this course, though the content will follow closely: Business Statistics, by E. Selvanathan, S. Selvanathan, and G. Keller, 7th 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. http://onlinestatbook.com/)

Calculator
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, www.myuni.adelaide.edu.au. 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 practicals.

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

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

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:

Watch lectures 2 hours per week

Attend practicals 1-2 hours per week

Study textbook and lecture notes 4 hours per week

Prepare homework answers 4 hours per week
##### 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. 1-6 Practicals Practicals will involve discussions, solving problem sets, and the use of statistical software (Stata) to address statistical problems. 1-6

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 Quizzes (Best 4 of 6 tests count towards final grade) Every fortnight 40% MCQs via MyUni 1-6 Group project Week 12 20% Written report and in-class presentation 1-6 Final exam Exam period 40% 2 hours via MyUni 1-6 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 in the practical in 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.

##### Submission
Quizzes are administered via MyUni. The group project is to be handed in on week 12, at the end of the student presentations.

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

M10 (Coursework Mark Scheme)
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.

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 studentâ€™s disciplinary procedures.

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

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