ENCN305-14S1 (C) Semester One 2014

Computer Programming and Stochastic Modelling

15 points

Details:
Start Date: Monday, 24 February 2014
End Date: Sunday, 29 June 2014
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 9 March 2014
  • Without academic penalty (including no fee refund): Sunday, 25 May 2014

Description

Programming in Matlab. Exploratory data analysis, model fitting, optimisation, maximum likelihood, residuals analysis, outlier detection, simulation, bootstrap methods.

Learning Outcomes

  • to improve students’ general programming skills, so they can develop solutions to engineering problems in Matlab and, potentially, in other procedural languages.
  • to give students particular familiarity with the Matlab environment and its relevance to engineering.
  • to introduce Monte Carlo simulation methods for solving statistical problems, in particular: functions of random variables whose input parameters are uncertain, and using bootstrap simulations to perform hypothesis tests to compare datasets with each other or with idealized models.
  • to introduce linear regression as a method to examine dependences between different quantities for which observational data is available.
  • to create stochastic models from observational data and use them for prediction of future observations, or scrutinize observational data with existing models.

Prerequisites

Course Coordinator / Lecturer

Nang Sze

Lecturer

Richard Lobb

Contact Person

Raazesh Sainudiin

Assessment

Assessment Due Date Percentage 
Assignment 1 (CP) 15%
Assignment 2 (SM) 7%
Assignment 3 (SM) 13%
final exam 40%
Learn Quizzzes (CP) 5%
Test (CP) 20%


The assessment for this paper will comprise four components – learn quizzes in the computer programming labs, assignments, a mid-semester test and the final exam. All of the material covered in the first component will be assessed in the mid-semester test. The second component will be tested in the final exam.

1. You cannot pass this course unless you achieve a mark of at least 40% in each of the mid-semester test and the final exam. A student who narrowly fails to achieve 40% in either the test or exam, but who performs very well in the other, may be eligible for a pass in the course.

2. All assignments must be submitted by the due date. Late submissions will not be accepted. If a student is unable to complete and submit an assignment by the deadline due to personal circumstances beyond their control they should discuss this with the lecturer involved as soon as possible.

3. Students in this course can apply for aegrotat consideration provided they have sat the mid-term test, the final exam or both.

4. Assignment work for the computer programming section must be done individually. However, the stochastic modelling assignments can be done individually or in pairs. If done in pairs a single submission for marking is required and both students receive the same mark. It is important that both students play an equal role in completing the assessment as the internal assessment is designed to prepare you for the formal assessments.

Indicative Fees

Domestic fee $841.00

International fee $4,638.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see Civil and Natural Resources Engineering .

All ENCN305 Occurrences

  • ENCN305-14S1 (C) Semester One 2014