UnitLevel 5Postgraduate

CIV5303 Applied transport data analysis

Faculty of Engineering

CIV5303 Applied transport data analysis is a level 5, 6-credit-point, postgraduate unit from the Faculty of Engineering, offered in 2021 in Semester 1 at Clayton. It has no prerequisites and unlocks 1 unit.

Credit points
6
Offered in 2021
Semester 1
Clayton
Assessment
No exam
3 tasks
Workload
150 hours
per semester

This is the 2021 handbook entry. See the 2027 entry.

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Requisites

Before CIV5303

No prerequisites or corequisites.

After CIV5303

1 unit list CIV5303 as a prerequisite or corequisite.

Overview

Data are fundamental to transport decision making. This unit applies rigorous probabilistic and statistical techniques to the analysis of data commonly encountered in transport studies. You will develop an understanding of probabilistic and statistical analysis procedures and their application to analysis of univariate and multivariate data, the model development process and its application to range of modelling techniques employed in the analysis of transport data.

Offerings in 2021

Teaching periodCampusMode
First semesterClaytonDe

Assessment

  • Assignment 1Threshold hurdle
    20%
  • Assignment 2Threshold hurdle
    30%
  • Final assessmentThreshold hurdle
    50%

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    Justify the relevance of quantitative data analysis skills for contemporary transport and traffic practice,

  2. 2

    Estimate and appraise suitable probabilistic models for transport and traffic problems,

  3. 3

    Infer the characteristics of a population based on a sample of that population drawing on appropriate statistical techniques, and

  4. 4

    Estimate and evaluate the robustness of statistical models for understanding current, or predicting/forecasting future, travel/traffic conditions.

Workload and teaching

  • Teaching approachProblem-based learning

Minimum total expected workload to achieve the learning outcomes for this unit is 150 hours per semester typically comprising a mixture of 4-6 hours of scheduled learning activities and 6-8 hours independent study per week. Scheduled activities may include a combination of teacher-directed learning, peer-directed learning and online engagement. Independent study may include associated readings, assessment and preparation for scheduled activities.

Learning resources

Required resources

Levine, D.M., Stephan, D.F. and Szabat, K.A. (2017) Statistics for Managers Using Microsoft Excel. 8th Edition. Global Edition. Pearson. Monash library resource.

Recommended resources

Spiegelman, C.H., Park, E.S. and Rilett, L.R. (2011) Transportation Statistics and Microsimulation. CRC Press. Monash library resource.

Technology resources

This unit will require you to become familiar with one computer software package that has statistical capabilities. The choice of package is your decision and will depend on what is available at your workplace or on your home computer. Excel has proven to be the most widely used software among students of this unit in previous years and was one reason why the required textbook was selected. However, you should be aware that Excel is a spreadsheet program with statistical add-ins and has been found to have flaws in some of the algorithms used. Other specialised statistical packages are available that are much more powerful and robust (e.g., SPSS, SAS, R).

Contacts

Unit Coordinators
Dr Wynita Griggs
Chief Examiners
Dr Wynita Griggs

Common questions

What are the prerequisites for CIV5303?

CIV5303 has no prerequisites.

What can I take after CIV5303?

CIV5303 is a prerequisite or corequisite for 1 unit, including CIV5308.

When is CIV5303 offered?

In 2021, CIV5303 runs in Semester 1 at Clayton.

How much work is CIV5303?

The handbook expects about 150 hours of study across the semester. No students have rated its difficulty yet.

Does CIV5303 have an exam?

No. CIV5303 has 3 assessment tasks and no exam.

More details

Credit points
6
Level
5
Study level
Postgraduate
Faculty
Faculty of Engineering
Organisational unit
Department of Civil and Environmental Engineering
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 2
Study abroad
Available