STATISTICAL METHODS

STA1STM

2021

Credit points: 15

Subject outline

In this subject you will be introduced to statistical methods which are frequently used in science, psychology, health science and the social sciences. Topics include descriptive treatment of sample data, elementary probability and distributions, estimation and hypothesis testing of means and proportions. Other topics may include sample survey techniques, introduction to regression and chi-squared distribution. The statistical package SPSS will also be introduced. The strengths and limitations of statistical models to enable informed thinking about sustainability are explored.

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorChristopher Lenard

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 1 - UG

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

PrerequisitesN/A

Co-requisitesN/A

Incompatible subjectsSTA1LS OR ECO1ISB OR STA1SS OR STA1CTS OR STA1PSY

Equivalent subjectsN/A

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Readings

The basic practice of statistics & CDR

Resource TypePrescribed

Resource RequirementN/A

AuthorMoore, DS, Notz, WI and Fligner, MA

Year2013

Edition/Volume6TH EDN

PublisherW.H. FREEMAN, NEW YORK.

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Career Ready

Career-focusedNo

Work-based learningNo

Self sourced or Uni sourcedN/A

Entire subject or partial subjectN/A

Total hours/days requiredN/A

Location of WBL activity (region)N/A

WBL addtional requirementsN/A

Graduate capabilities & intended learning outcomes

Graduate Capabilities

Intended Learning Outcomes

01. Summarise, numerically, graphically, and in words, the distribution of a data-set.
02. Describe and justify appropriate and reliable methods for gathering data via surveys and experiments.
03. Solve basic probability problems involving the normal distribution, and interpret the results within a specific context.
04. Analyse data using appropriate methods, including confidence intervals, hypothesis tests based on one and two sample means and matched pairs, and chi-squared tests.
05. Use simple linear regression and correlation to describe data and make predictions based on that data.
06. Perform basic statistical analyses using the software SPSS as a tool.
07. Communicate effectively in both technical and non-technical written language the results of statistical analyses.

Subject options

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Start date between: and    Key dates

Bendigo, 2021, Semester 2, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorChristopher Lenard

Class requirements

LectureWeek: 30 - 42
Three 1.00 h lecture per week on weekdays during the day from week 30 to week 42 and delivered via face-to-face.

WorkShopWeek: 30 - 42
One 1.00 h workshop per week on weekdays during the day from week 30 to week 42 and delivered via face-to-face.

Assessments

Assessment elementCommentsCategoryContributionHurdle% ILO*

One 3-hour examination (3000 words equivalent)Hurdle requirement: To pass the subject, a pass in the examination is mandatory.

N/AN/AN/AYes60 SILO1, SILO2, SILO3, SILO4, SILO5, SILO6, SILO7

One 30 minute computer lab test (500 words equivalent)

N/AN/AN/ANo10 SILO6, SILO7

Two 30 minute written tests (Test 1-10%, Test 2-20%) (500 words equivalent each, 1000 words total)

N/AN/AN/ANo30 SILO1, SILO2, SILO3, SILO4, SILO5, SILO6, SILO7