# 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.

SchoolSchool Engineering&Mathematical Sciences

Credit points15

Subject Co-ordinatorDavid Farchione

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

Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsFSTE First Year Survival Guide (second edition)RecommendedFaculty of Science, Technology and EngineeringLA TROBE UNIVERSITY 2012
ReadingsIntroductory Statistics: a problem-solving approachRecommendedKokoska, S 2011FREEMAN

## 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.

## Subject options

Select to view your study options…

Start date between: and    Key dates

## Melbourne, 2017, Semester 2, Day

### Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorDavid Farchione

### Class requirements

Computer Laboratory Week: 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.

Lecture Week: 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.

Practical Week: 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.

Lecture Week: 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.