Course Title: Practice of Analytics

Part A: Course Overview

Course Title: Practice of Analytics

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH2392

City Campus

Undergraduate

171H School of Science

Face-to-Face

 Sem 2 2020,
Sem 2 2021,
Sem 2 2022

Course Coordinator: Dr. Xu Zhang

Course Coordinator Phone: NA

Course Coordinator Email: xu.zhang@rmit.edu.au

Course Coordinator Availability: By appointment, by email


Pre-requisite Courses and Assumed Knowledge and Capabilities

None


Course Description

Practice of Analytics is a course that aims in developing applied skills using several different statistical software.   This course introduces you to the concepts and the different software, focusing on their differences and their usefulness in relation to the data in consideration.   An introduction to the available statistical software and analytics tools will be provided and practical aspect on data analytics will be applied. 


Objectives/Learning Outcomes/Capability Development

This course contributes to the following Program Learning Outcomes for BP083 Bachelor of Applied Mathematics and Statistics:   PLO2. Knowledge and technical competence • The ability to use the appropriate software and modern computational tools to apply basic analytics methodologies   PLO3. Problem-solving • The ability to bring together and flexibly apply knowledge to characterise, analyse and solve a wide range of problems 


On completion of this course you will be able to:

  1. Know the available tools for practical analytic and be able to use them effectively.
  2. Perform basic statistical analysis using a statistical software.
  3. Use a statistical software in an efficient way.
  4. Apply known statistical techniques in real data.
  5. Develop strategies and using several available analytical tools to inference from data of various types.


Overview of Learning Activities

You will be actively engaged in a range of learning activities such as lectorials, tutorials, practicals, laboratories, seminars, project work, class discussion, individual and group activities. Delivery may be face to face, online or a mix of both.

You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, and through links and material specific to this course that is available through myRMIT Studies Course.


Overview of Learning Resources

RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course.

There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.

Library Subject Guide for Mathematics & Statistics http://rmit.libguides.com/mathstats  


Overview of Assessment

 

Assessment Tasks

Assessment Task 1: Assignments
Weighting 15%
This assessment task supports CLOs 1, 2, 3, 4 & 5

Assessment Task 2: Lab Assignments - related to usage of computer software
Weighting 15%
This assessment task supports CLOs 1, 2, 3, 4 & 5

Assessment Task 3: Project
Weighting 20%
This assessment task supports CLOs 1, 2, 3, 4 & 5

Assessment Task 4: Final Exam
Weighting 50%
This assessment task supports CLOs 1, 2, 3, 4 & 5

If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.