PSYCHOLOGICAL RESEARCH METHODS

PSY2PRM

2018

Credit points: 15

Subject outline

The two parts of this subject deal with statistical inferences that we can make about (1) relationships between measures gathered from a single group of participants and (2) differences in the group means on one variable gathered from two or more groups of participants. In the first part, we start with correlation between variables and move on to more advanced regression topics of using several variables to predict an outcome. In the second part, we start with the basic principles of experimental design to compare data gathered from the same or different groups of participants. We study the Analysis of Variance (ANOVA) in detail, on how we can use it to establish differences between several groups and, following that, how we can compare means between groups.

SchoolSchool of Psychology & Public Health

Credit points15

Subject Co-ordinatorStacey Rich

Available to Study Abroad StudentsYes

Subject year levelYear Level 2 - UG

Exchange StudentsYes

Subject particulars

Subject rules

Prerequisites (One of PSY1EFP or PSY1PYA) and (One of PSY1CFP or PSY1PYB) and (One of STA1PSY, STA1STM, STA1CTS) or by approval from the subject coordinator.

Co-requisitesN/A

Incompatible subjects PSY2PYA, PSY2PYB

Equivalent subjectsN/A

Special conditionsN/A

Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsDiscovering Statistics Using IBM SPSS Statistics ED. 5RecommendedAndy Field, 2017Sage

Graduate capabilities & intended learning outcomes

01. Select the statistical techniques that are appropriate to the research hypotheses being tested.

Activities:
Task: Determine the level of measurement of data being analysed and select the appropriate statistical tests that will answer the research questions. Formative: Parts of two of 12 tutorial class exercises Formative and Summative: 50% assessed in two assignments on data analysis. Summative: Exam.
Related graduate capabilities and elements:
Critical Thinking (Critical Thinking)
Quantitative Literacy/ Numeracy (Quantitative Literacy/ Numeracy)
Inquiry/ Research (Inquiry/ Research)
Creative Problem-solving (Creative Problem-solving)

02. Prepare data to meet the distributional assumptions of statistical tests.

Activities:
Task: Assess and, if required, transform the distributional characteristics of variables. Formative: Parts of two of 12 tutorial class exercises. Formative and Summative: 50% assessed in two assignments on data analysis. Summative: Exam.
Related graduate capabilities and elements:
Quantitative Literacy/ Numeracy (Quantitative Literacy/ Numeracy)
Critical Thinking (Critical Thinking)
Inquiry/ Research (Inquiry/ Research)

03. Use software for statistical computing and select the appropriate analytical and output options.

Activities:
Task: Conduct tests of correlation, regression, analyses of variance and further post hoc tests, using software for statistical computing. Formative: Parts of six of 12 tutorial class exercises. Formative and Summative: 50% assessed in two assignments on data analysis.
Related graduate capabilities and elements:
Quantitative Literacy/ Numeracy (Quantitative Literacy/ Numeracy)
Inquiry/ Research (Inquiry/ Research)
Critical Thinking (Critical Thinking)

04. Select and conduct correlational analyses to analyse relationships between variables and Analyses of Variance to analyse differences between means.

Activities:
Task: Select and perform statistical techniques appropriate to the research question on relationships and on differences between means. Formative: Parts of six of 12 tutorial class exercises. Formative and Summative: 50% assessed in two assignments on data analysis. Summative: Exam.
Related graduate capabilities and elements:
Quantitative Literacy/ Numeracy (Quantitative Literacy/ Numeracy)
Inquiry/ Research (Inquiry/ Research)
Writing (Writing)
Critical Thinking (Critical Thinking)
Discipline-specific GCs (Discipline-specific GCs)

05. Interpret and report on the outcome of statistical tests in APA format.

Activities:
Task: Interpreting and reporting the results of statistical analyses in APA format. Formative: Parts of six of 12 tutorial class exercises. Formative and Summative: 50% assessed in two assignments on data analysis. Summative: Exam.
Related graduate capabilities and elements:
Writing (Writing)
Inquiry/ Research (Inquiry/ Research)
Quantitative Literacy/ Numeracy (Quantitative Literacy/ Numeracy)
Discipline-specific GCs (Discipline-specific GCs)
Critical Thinking (Critical Thinking)

Subject options

Select to view your study options…

Start date between: and    Key dates

Albury-Wodonga, 2018, Semester 1, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorStacey Rich

Class requirements

Lecture Week: 10 - 22
Two 1.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via online.
"Lectures online from Week 1"

Tutorial Week: 11 - 21
One 2.0 hours tutorial per week on weekdays during the day from week 11 to week 21 and delivered via face-to-face.

Lecture Week: 10 - 22
Three 1.0 hours lecture per study period on weekdays during the day from week 10 to week 22 and delivered via video conference.
"Lecture held in weeks 1, 6, 12"

Assessments

Data Analysis Assignments (2 x 1000 words)50 01, 02, 03, 04, 05
Exam (1 x 2 hours)72 items per 1 occasion. Equates to < 2000words40 01, 02, 04, 05
Quiz (4 during semester)5 items per 4 occasions. Equates to < 500 words in total.10 01, 02, 03, 04, 05

Bendigo, 2018, Semester 1, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorStacey Rich

Class requirements

Lecture Week: 10 - 22
Two 1.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via online.

Tutorial Week: 11 - 21
One 2.0 hours tutorial per week on weekdays during the day from week 11 to week 21 and delivered via face-to-face.

Lecture Week: 10 - 22
Three 1.0 hours lecture per study period on weekdays during the day from week 10 to week 22 and delivered via video conference.
"Lectures deliverd Weeks 1, 6, 12"

Assessments

Data Analysis Assignments (2 x 1000 words)50 01, 02, 03, 04, 05
Exam (1 x 2 hours)72 items per 1 occasion. Equates to < 2000words40 01, 02, 04, 05
Quiz (4 during semester)5 items per 4 occasions. Equates to < 500 words in total.10 01, 02, 03, 04, 05

Melbourne, 2018, Semester 1, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorStacey Rich

Class requirements

Lecture Week: 10 - 22
Two 1.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via online.

Tutorial Week: 11 - 21
One 2.0 hours tutorial per week on weekdays during the day from week 11 to week 21 and delivered via face-to-face.

Lecture Week: 10 - 22
Three 1.0 hours lecture per study period on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
"Lectures occur in Weeks 1,6, 12"

Assessments

Data Analysis Assignments (2 x 1000 words)50 01, 02, 03, 04, 05
Exam (1 x 2 hours)72 items per 1 occasion. Equates to < 2000words40 01, 02, 04, 05
Quiz (4 during semester)5 items per 4 occasions. Equates to < 500 words in total.10 01, 02, 03, 04, 05

Online, 2018, Summer 1, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorBrad Wright

Class requirements

Lecture Week: 46
Two 1.0 hours lecture per week on weekdays during the day in week 46 and delivered via online.

Tutorial Week: 46
One 2.0 hours tutorial per week on weekdays during the day in week 46 and delivered via online.
"Collaborate tutorial. Enrolled students will use the collaborate program and have SPSS software installed on their personal computers"