# APPLIED STATISTICAL METHODS

STA2ASM

2018

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.

SchoolSchool Engineering&Mathematical Sciences

Credit points15

Subject Co-ordinatorAgus Salim

Subject year levelYear Level 2 - UG

Exchange StudentsYes

## Subject particulars

### Subject rules

Prerequisites STA1PSY or STA1LS or STA1SS

Co-requisitesN/A

Incompatible subjects STA2AS, STA2MS, STA2RSP, STA2AMS, STA2ABS

Equivalent subjectsN/A

Special conditionsN/A

Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsApplied Statistical MethodsPrescribedLuke Prendergast 2018La Trobe University
ReadingsFundamentals of Biostatistics 8th EdRecommendedRosner B, 2016CENAGE

## Graduate capabilities & intended learning outcomes

01. Apply appropriate statistical and probabilistic methods for data analysis.

Activities:
Discussed and demonstrated in lectures and lecture/workshops. Related problems solved by students in practice classes. Assignment questions, with feedback.

02. Discuss the importance of "thinking ahead" when planning and designing experiments.

Activities:
Discussed and demonstrated in lectures and lecture/workshops. Related problems solved by students in practice classes. Assignment questions, with feedback.

03. Execute statistical software functionality for data analysis and interpret the output accurately and meaningfully.

Activities:
Some discussion in lectures and lecture/workshops. Related problems solved by students in computer laboratory classes. Computer laboratory project, with guidance and feedback.

04. Assess the effectiveness of statistical methods using simulation.

Activities:
Some discussion in lectures and lecture/workshops. Related problems solved by students in computer laboratory classes. Computer laboratory project, with guidance and feedback.

05. Explain the codes of conduct that govern professional competence and integrity in the field of statistics.

Activities:
Discussed and demonstrated in lectures and lecture/workshops.

06. Formulate hypothesis testing related to biological and medical problems; draw and explain the conclusions that follow from a rigorous and systematic analysis.

Activities:
Discussed and demonstrated in lectures and lecture/workshops. Related problems solved by students in practice classes. Assignment questions, with feedback.

## Subject options

Select to view your study options…

Start date between: and    Key dates

## Melbourne, 2018, Semester 1, Day

### Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorAgus Salim

### Class requirements

Lecture/Workshop Week: 10 - 22
One 1.0 hours lecture/workshop per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
"Recorded on Echo"

Lecture Week: 10 - 22
One 1.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
"Recorded on Echo"

Practical Week: 11 - 22
One 1.0 hours practical per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.

Computer Laboratory Week: 11 - 22
One 1.0 hours computer laboratory per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.