STATISTICAL SCIENCE
STA1SS
2017
Credit points: 15
Subject outline
This subject provides an introduction to applied and theoretical statistics. (The applied component of this subject is identical to the content covered in STA1LS.) It introduces students to the basic applied statistical methods used in the biological sciences, medical sciences, agricultural sciences, nutrition, and health sciences and also provides an introduction to the mathematical theory used in the area of statistics. The three main areas of study are descriptive statistics, probability, and statistical inference and the use of a statistical computing package is an integral part of this subject. This subject is a possible pre-requisite for the second-year subjects in statistics.
School: School Engineering&Mathematical Sciences
Credit points: 15
Subject Co-ordinator: David Farchione
Available to Study Abroad Students: Yes
Subject year level: Year Level 1 - UG
Exchange Students: Yes
Subject particulars
Subject rules
Prerequisites: Year-12 mathematics.
Co-requisites: N/A
Incompatible subjects: STA1LS; STA1PSY; STA1IDA; STA1STM; STA1CTS; ECO1ISB
Equivalent subjects: N/A
Special conditions: N/A
Learning resources
Readings
| Resource Type | Title | Resource Requirement | Author and Year | Publisher |
|---|---|---|---|---|
| Readings | FSTE First Year Survival Guide (second edition) | Recommended | Faculty of Science, Technology and Engineering | LA TROBE UNIVERSITY 2012 |
| Readings | Introductory Statistics: a problem-solving approach | Recommended | Kokoska, S 2011 | FREEMAN |
Graduate capabilities & intended learning outcomes
01. Convert data into information by using appropriate numerical and graphical summaries.
- Activities:
- Lectures: In the lectures we introduce the basic statistical tools used in statistics and apply these tools to practical examples in the Life Sciences discipline. Practice Classes: Students work through practical examples by applying the concepts and techniques learnt in the lectures. Computer Labs: Students use the SPSS statistical computer package to work through practical examples.
02. Calculate probabilities and other quantities from discrete and continuous probability distributions and by applying the basic rules of probability.
- Activities:
- Lectures: In the lectures we introduce the basic statistical tools used in statistics and apply these tools to practical examples in the Life Sciences discipline. Practice Classes: Students work through practical examples by applying the concepts and techniques learnt in the lectures. Computer Labs: Students use the SPSS statistical computer package to work through practical examples.
03. Identify and apply appropriate statistical inference methods for decision making.
- Activities:
- Lectures: In the lectures we introduce the basic statistical tools used in statistics and apply these tools to practical examples in the Life Sciences discipline. Practice Classes: Students work through practical examples by applying the concepts and techniques learnt in the lectures. Computer Labs: Students use the SPSS statistical computer package to work through practical examples.
04. Compute, display and interpret numerical and graphical summaries, probabilities and various statistical inference procedures using the statistical software package SPSS.
- Activities:
- Lectures: In the lectures we introduce the basic statistical tools used in statistics and apply these tools to practical examples in the Life Sciences discipline. Computer Labs: Students use the SPSS statistical computer package to work through practical examples.
05. Apply basic mathematical theoretical techniques in the area of statistics.
- Activities:
- Lectures: In the lectures we introduce basic mathematical theory in the area of statistics. Practice Classes: Students work through examples using basic theoretical techniques learnt in the lectures.
Melbourne, 2017, Semester 2, Day
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Enrolment information:
Subject Instance Co-ordinator: David Farchione
Class requirements
Computer LaboratoryWeek: 31 - 43
One 1.0 hours computer laboratory per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
LectureWeek: 31 - 43
One 2.0 hours lecture per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
PracticalWeek: 31 - 43
One 1.0 hours practical per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
LectureWeek: 31 - 43
One 1.0 hours lecture per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| One 3-hour examination | 60 | 01, 02, 03, 04, 05 | |
| Five assignments (equivalent to 1500 words) | 40 | 01, 02, 03, 04, 05 |