sta1stm statistical methods

STATISTICAL METHODS

STA1STM

2020

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 (Pre 2022)

Credit points15

Subject Co-ordinatorChristopher Lenard

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 1 - UG

Exchange StudentsNo

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

PrerequisitesN/A

Co-requisitesN/A

Incompatible subjectsSTA1SS OR ECO1ISB OR STA1LS OR STA1PSY OR STA1CTS

Equivalent subjectsN/A

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Learning resources

The basic practice of statistics & CDR

Resource TypeBook

Resource RequirementPrescribed

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

INQUIRY AND ANALYSIS - Critical Thinking and Problem Solving

INQUIRY AND ANALYSIS - Research and Evidence-Based Inquiry

PERSONAL AND PROFESSIONAL - Ethical and Social Responsibility

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

Select to view your study options…

Bendigo, 2020, Semester 2, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment informationN/A

Subject Instance Co-ordinatorChristopher Lenard

Class requirements

LectureWeek: 31 - 43
Three 1.00 hour lecture per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.

WorkShopWeek: 31 - 43
One 1.00 hour workshop per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.

Assessments

Assessment element	Comments	Category	Contribution	Hurdle	%	ILO*
One 3-hour examination (3000 words equivalent)Hurdle requirement: To pass the subject, a pass in the examination is mandatory.	N/A	N/A	N/A	Yes	60	SILO1, SILO2, SILO3, SILO4, SILO5, SILO6, SILO7
One 30 minute computer lab test (500 words equivalent)	N/A	N/A	N/A	No	10	SILO6, SILO7
Two 30 minute written tests (Test 1-10%, Test 2-20%) (500 words equivalent each, 1000 words total)	N/A	N/A	N/A	No	30	SILO1, SILO2, SILO3, SILO4, SILO5, SILO6, SILO7