sta1ss statistical science
STATISTICAL SCIENCE
STA1SS
2018
Credit points: 15
Subject outline
This subjectprovides an introduction to applied and theoretical statistics. (The appliedcomponent of this subject is identical to the content covered in STA1LS.) Itintroduces students to the basic applied statistical methods used in the biological sciences, medicalsciences, agricultural sciences, nutrition, and health sciences and also provides an introduction to themathematical theory used in the area of statistics. The three main areas ofstudy are descriptivestatistics, probability, and statistical inference and theuse of a statistical computing package is an integral part of this subject. The strengths and limitations of statisticalmodels to enable informed thinking about sustainability are explored. This subject is a possible pre-requisitefor the second-year subjects in statistics.
SchoolSchool Engineering&Mathematical Sciences
Credit points15
Subject Co-ordinatorDavid Farchione
Available to Study Abroad StudentsYes
Subject year levelYear Level 1 - UG
Exchange StudentsYes
Subject particulars
Subject rules
Prerequisites Year-12 mathematics.
Co-requisitesN/A
Incompatible subjects STA1LS; STA1PSY; STA1IDA; STA1STM; STA1CTS; ECO1ISB
Equivalent subjectsN/A
Special conditionsN/A
Learning resources
Readings
| Resource Type | Title | Resource Requirement | Author and Year | Publisher |
|---|---|---|---|---|
| Readings | Introductory Statistics: a problem-solving approach, 2nd ed. | Recommended | Kokoska, S. (2015). | FREEMAN |
| Readings | Manual for SPSS and R with Examples from the Life Sciences | Prescribed | Farchione, D. (2018) | La Trobe |
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.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Quantitative Literacy)
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.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Quantitative Literacy)
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.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Quantitative Literacy)
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.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Quantitative Literacy)
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.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Quantitative Literacy)
Subject options
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Melbourne, 2018, Semester 2, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorDavid Farchione
Class requirements
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.
Unscheduled Online ClassWeek: 31 - 43
One 1.0 hours unscheduled online class per week on weekdays during the day from week 31 to week 43 and delivered via online.
"The unscheduled online class will involve readings that describe the basics of statistical theory. These readings are accompanied by video clips that help explain the theory."
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.
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 |