## ECON 1008OUA - Data Analytics I

### OUA - Trimester 1 - 2023

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, though these tools are also useful in many other real-world settings. The focus is on concepts, reasoning, interpretation, and thinking that build upon computation, formulae and theory. Students will be required to clearly and effectively communicate and visualize their ideas, analyses, and results. The course covers two main branches of statistical data analysis: descriptive statistics and inferential statistics. Descriptive statistics includes data collection, exploration, and interpretation through numerical and graphical techniques such as charts and visual representations. Inferential statistics includes the selection and application of correct and suitable statistical techniques in order to make estimates or test claims about data based on a sample. By the end of this course, students should understand and know how to use statistics in real-world settings. Students will also develop some understanding of the limitations and misuse of statistical inference as well as the ethics of data analysis and statistics.

• General Course Information
##### Course Details
Course Code ECON 1008OUA Data Analytics I Economics Trimester 1 Undergraduate OUA 3 Up to 3 hours per week N ECON 1011, ECON 1008UAC, ECON 1008UACM, STATS 1000, STATS 1005, STATS 1004, STATS 1504 Available only to University of Adelaide Open Universities Australia students Typically, tutorial participation and/or exercises, assignments, tests and final exam
##### Course Staff

Course Coordinator: Dr Florian Ploeckl

##### 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 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.

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.

1,2,4

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.

1,2,3,4

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.

2,4

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

1,2,3,4

Attribute 5: Intercultural and ethical competency

Graduates are responsible and effective global citizens whose personal values and practices are consistent with their roles as responsible members of society.

2,3,4

Attribute 7: Digital capabilities

Graduates are well prepared for living, learning and working in a digital society.

1,2,3,4

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.

2,4
• Learning Resources
##### Recommended Resources
Text book

Selvanathan S, Selvanathan S and Keller G, Business Statistics: Australia New Zealand Edition 8
ISBN 9780170439527
##### Online Learning
Weekly Modules on MyUni contain extensive learning material covering the module topics completely. This includes videos, explanations, exercises, and other components.

There are discussion boards on MyUni. Weekly questions provide another element to familiarize students with the real-world application of the materials as well as provide a way for students to interact with each other and teaching staff.
• Learning & Teaching Activities
##### Learning & Teaching Modes
This course uses self-study modules plus tutorials.

The self-study modules provide a comprehensive overview of the material through the use of different media, including written explanations, videos, animations, examples, and exercises

The weekly one-hour tutorials provide students with the opportunity to discuss and explore the relevance and application of the material. Additionally, practical exercises of the quantitative tools and methods in this course will be practised.

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

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 equates to approximately 12 hours per week per course. This time commitment includes doing the relevant readings, preparing for online tutorials, other on-line activities and assessment tasks.
##### Learning Activities Summary
The topics to be covered (subject to changes) are:

Module 1: Introduction to Statistics & Data Analytics

Module 2: Graphically Analysing Data

Module 3: Analysing Data Numerically

Module 4: Probability & Chance

Module 5: Probability Distributions

Module 6: Sampling Distributions

Module 7: Estimation

Module 8: Hypothesis Testing

Module 9: Estimation & Hypothesis Testing with Two Populations

Module 10: Covariance & Correlation

Module 11: Linear Regression

Module 12: Subject Review
• 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 Weight Length Learning Outcomes Weekly Quizzes Weekly 20% MCQ 1-4 Assignments Weeks 4, 9, and 12 80% (25%,30%,25%) 1200-2000 words 1-4
##### Assessment Detail
Weekly Quiz

Each module contains a multiple choice quiz, which is due at the end of the module week. The best 10 out of 12 quizzes count with equal weight.

Major Assignments

There are three major written assignments. Each assignment consists of quantitative exercises involving written explanations.
##### Submission
All submissions will be done on MyUni

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.

• 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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