APPLIED STATISTICAL METHODS
STA2ASM
2020
Credit points: 15
Subject outline
Building on the understanding of applied statistical methods developed in first year statistics subjects, STA2ASM provides an understanding of these methods at an intermediate level. The subject places a special emphasis on applications of statistics to biological and medical problems. There are specific questions in the assignments, project, test and examination that reflect such an emphasis. This subject does not require a knowledge of calculus. An introduction to the open source statistical computing package R is included.
School: Engineering and Mathematical Sciences (Pre 2022)
Credit points: 15
Subject Co-ordinator: David Farchione
Available to Study Abroad/Exchange Students: Yes
Subject year level: Year Level 2 - UG
Available as Elective: No
Learning Activities: N/A
Capstone subject: No
Subject particulars
Subject rules
Prerequisites: STA1SS OR STA1LS OR STA1PSY
Co-requisites: N/A
Incompatible subjects: STA2AMS OR STA2RSP OR STA2AS OR STA2ABS
Equivalent subjects: N/A
Quota Management Strategy: N/A
Quota-conditions or rules: N/A
Special conditions: N/A
Minimum credit point requirement: N/A
Assumed knowledge: N/A
Learning resources
Fundamentals of Biostatistics
Resource Type: Book
Resource Requirement: Recommended
Author: Rosner B
Year: 2016
Edition/Volume: 8th Ed
Publisher: CENAGE
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Applied Statistical Methods
Resource Type: Book
Resource Requirement: Prescribed
Author: Luke Prendergast
Year: 2018
Edition/Volume: N/A
Publisher: La Trobe University
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Career Ready
Career-focused: No
Work-based learning: No
Self sourced or Uni sourced: N/A
Entire subject or partial subject: N/A
Total hours/days required: N/A
Location of WBL activity (region): N/A
WBL addtional requirements: N/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Melbourne (Bundoora), 2020, Semester 1, Day
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: David Farchione
Class requirements
Computer LaboratoryWeek: 11 - 22
One 1.00 hour computer laboratory per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.
LectureWeek: 10 - 22
One 1.00 hour lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Recorded on Echo
Lecture/WorkshopWeek: 10 - 22
One 1.00 hour lecture/workshop per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Recorded on Echo
PracticalWeek: 11 - 22
One 1.00 hour practical per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | ILO* |
|---|---|---|---|---|---|
2 hour exam (equivalent to 2000 words) | N/A | N/A | No | 55 | SILO1, SILO2, SILO5, SILO6 |
Four written assignments (equivalent to 200 words each, 800 words total) | N/A | N/A | No | 20 | SILO1, SILO2, SILO6 |
In-class computer test (equivalent to 600 words) | N/A | N/A | No | 15 | SILO3, SILO4 |
Statistical computing project (equivalent to 400 words) | N/A | N/A | No | 10 | SILO3, SILO4 |