stm2eps engineering probability and statistics
ENGINEERING PROBABILITY AND STATISTICS
STM2EPS
2016
Credit points: 15
Subject outline
This subject develops an understanding of probability and statistics applied to engineering problems. Probability topics include joint and conditional probability, Bayes' Theorem and distributions such as the uniform,binomial, Poisson and normal distributions as well as properties of random variables and the Central Limit Theorem. Statistical inference and data analysis is also considered covering, among other topics, significance testing and confidence intervals with an introduction to methods such as ANOVA, linear and nonlinear regression and model verification. Applications to engineering such as queuing theory, reliability and efficiency of processes are considered throughout. Students will work to achieve the stage one competencies 1.2(conceptual understanding of the underpinning mathematics, numerical analysis and statistics), 2.2 (fluent application of engineering techniques, tools and resources) and 3.2 (effective written communication).
SchoolSchool Engineering&Mathematical Sciences
Credit points15
Subject Co-ordinatorLuke Prendergast
Available to Study Abroad StudentsYes
Subject year levelYear Level 2 - UG
Exchange StudentsYes
Subject particulars
Subject rules
Prerequisites Must be enrolled in Bachelor of Engineering (Honours) SHENG.
Co-requisitesN/A
Incompatible subjectsN/A
Equivalent subjectsN/A
Special conditions This subject is only available to students enrolled in Bachelor of Engineering degree.
Learning resources
Readings
| Resource Type | Title | Resource Requirement | Author and Year | Publisher |
|---|---|---|---|---|
| Readings | Online learning materials | Prescribed | Luke Prendergast 2016 | La Trobe University |
Graduate capabilities & intended learning outcomes
01. Identify probabilistic traits of engineering problems and choose methods which can be employed to determine valid and informative solutions.
- Activities:
- Modeled in online readings and videos and practised in tutorials.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Writing,Quantitative Literacy)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
02. Defend or question the validity of probability models applied to problems including, but not limited to, system and structural reliability, queuing theory and signal processing.
- Activities:
- Modeled in online readings and videos and practised in tutorials.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Writing,Quantitative Literacy)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
03. Demonstrate an ability to solve a variety of engineering problems using applications of probability models.
- Activities:
- Modeled in online readings and videos and practised in tutorials and computer lab classes.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Writing,Quantitative Literacy)
- Literacies and Communication Skills(Writing,Quantitative Literacy)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
04. Define a statistical hypothesis with applications to engineering that may be tested using data.
- Activities:
- Modeled in online readings and videos and practised in tutorials and computer lab classes.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Writing,Quantitative Literacy)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
05. Identify and apply statistical methods for hypothesis testing and estimation with applications in engineering that include, but are not limited to, quality control, reliability and efficiency of processing.
- Activities:
- Modeled in online readings and videos and practised in tutorials and computer lab classes.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Writing,Quantitative Literacy)
- Literacies and Communication Skills(Writing,Quantitative Literacy)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
06. Present clear, well-structured summaries of findings, both probabilistic and data-based, using appropriate mathematical and statistical vocabulary.
- Activities:
- Modeled in online readings and videos and practised in tutorials and computer lab classes.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Writing,Quantitative Literacy)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
Subject options
Select to view your study options…
Bendigo, 2016, Semester 2, Blended
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorLuke Prendergast
Class requirements
Computer LaboratoryWeek: 31 - 43
One 2.0 hours computer laboratory every two weeks on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
"Even Teaching Weeks"
PracticalWeek: 31 - 43
One 2.0 hours practical every two weeks on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
"Odd teaching weeks"
LectureWeek: 31 - 43
One 2.0 hours lecture per week on weekdays during the day from week 31 to week 43 and delivered via online.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| Five Online Quizzes | Each quiz may be attempted a maximum of three times. The highest mark achieved for the up-to-three attempts is awarded. Word-equivalence: 500 words. | 10 | 01, 03, 05 |
| Four assignments, submitted online | Word-equivalence: 500 words each (total 2000 words). | 40 | 01, 02, 03, 04, 05, 06 |
| Two hour Final Exam | Word-equivalence: 2000 words. | 50 | 01, 02, 03, 04, 05, 06 |
Melbourne, 2016, Semester 2, Blended
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorLuke Prendergast
Class requirements
Computer LaboratoryWeek: 31 - 43
One 2.0 hours computer laboratory every two weeks on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
"Even Teaching Weeks"
PracticalWeek: 31 - 43
One 2.0 hours practical every two weeks on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
"Odd teaching weeks"
LectureWeek: 31 - 43
One 2.0 hours lecture per week on weekdays during the day from week 31 to week 43 and delivered via online.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| Five Online Quizzes | Each quiz may be attempted a maximum of three times. The highest mark achieved for the up-to-three attempts is awarded. Word-equivalence: 500 words. | 10 | 01, 03, 05 |
| Four assignments, submitted online | Word-equivalence: 500 words each (total 2000 words). | 40 | 01, 02, 03, 04, 05, 06 |
| Two hour Final Exam | Word-equivalence: 2000 words. | 50 | 01, 02, 03, 04, 05, 06 |