School: Science

This unit information may be updated and amended immediately prior to semester. To ensure you have the correct outline, please check it again at the beginning of semester.

  • Unit Title

    Applied Multivariate Statistics
  • Unit Code

    MAT6104
  • Year

    2021
  • Enrolment Period

    1
  • Version

    1
  • Credit Points

    20
  • Full Year Unit

    N
  • Mode of Delivery

    On Campus
    Online
  • Unit Coordinator

    Dr Ebenezer AFRIFA-YAMOAH

Description

In this unit students will develop understanding of the theory and techniques of multivariate statistical analyses and their applications in areas such as health, biological, environmental and data science. This unit will prepare students for real world data analysis in industry and research.

Prerequisite Rule

Students must have passed MAT5212 and MAT6105 or equivalent.

Learning Outcomes

On completion of this unit students should be able to:

  1. Apply multifactor and multivariate techniques to solve problems related to multivariate data sets.
  2. Use critical thinking skills with regard to the modelling of multi-factor and multivariate data in an individual and collaborative setting.
  3. Implement statistical analysis using appropriate software.
  4. Communicate multi-factor and multivariate statistical theories, principles and techniques.

Unit Content

  1. Methods of ordination including multidimensional scaling.
  2. Role of data structures, statistical distributions and models in scientific investigations.
  3. Methods of classification including discriminant analysis and cluster analysis.
  4. Factor Analysis: principal components and their properties, principal component analysis, the factor analysis model.
  5. Comparison of multivariate means via hypothesis testing and confidence regions.
  6. Regression Analysis: the multiple linear regression model, least squares estimation, analysis of residuals, model building, coefficient of determination, selection of a subset of regressors.

Assessment

GS1 GRADING SCHEMA 1 Used for standard coursework units

Students please note: The marks and grades received by students on assessments may be subject to further moderation. All marks and grades are to be considered provisional until endorsed by the relevant School Progression Panel.

ON CAMPUS
TypeDescriptionValue
AssignmentAssignment on the implementation of statistical analysis40%
ReportReport on analysis of real data set40%
PresentationVideo presentation20%
ONLINE
TypeDescriptionValue
AssignmentAssignment on the implementation of statistical analysis40%
ReportReport on analysis of real data set40%
PresentationVideo presentation20%

Disability Standards for Education (Commonwealth 2005)

For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Access and Inclusion website.

Academic Misconduct

Edith Cowan University has firm rules governing academic misconduct and there are substantial penalties that can be applied to students who are found in breach of these rules. Academic misconduct includes, but is not limited to:

  • plagiarism;
  • unauthorised collaboration;
  • cheating in examinations;
  • theft of other students' work;

Additionally, any material submitted for assessment purposes must be work that has not been submitted previously, by any person, for any other unit at ECU or elsewhere.

The ECU rules and policies governing all academic activities, including misconduct, can be accessed through the ECU website.

MAT6104|1|1

School: Science

This unit information may be updated and amended immediately prior to semester. To ensure you have the correct outline, please check it again at the beginning of semester.

  • Unit Title

    Applied Multivariate Statistics
  • Unit Code

    MAT6104
  • Year

    2021
  • Enrolment Period

    2
  • Version

    1
  • Credit Points

    20
  • Full Year Unit

    N
  • Mode of Delivery

    On Campus
    Online
  • Unit Coordinator

    Dr Ebenezer AFRIFA-YAMOAH

Description

In this unit students will develop understanding of the theory and techniques of multivariate statistical analyses and their applications in areas such as health, biological, environmental and data science. This unit will prepare students for real world data analysis in industry and research.

Prerequisite Rule

Students must have passed MAT5212 and MAT6105 or equivalent.

Learning Outcomes

On completion of this unit students should be able to:

  1. Apply multifactor and multivariate techniques to solve problems related to multivariate data sets.
  2. Use critical thinking skills with regard to the modelling of multi-factor and multivariate data in an individual and collaborative setting.
  3. Implement statistical analysis using appropriate software.
  4. Communicate multi-factor and multivariate statistical theories, principles and techniques.

Unit Content

  1. Methods of ordination including multidimensional scaling.
  2. Role of data structures, statistical distributions and models in scientific investigations.
  3. Methods of classification including discriminant analysis and cluster analysis.
  4. Factor Analysis: principal components and their properties, principal component analysis, the factor analysis model.
  5. Comparison of multivariate means via hypothesis testing and confidence regions.
  6. Regression Analysis: the multiple linear regression model, least squares estimation, analysis of residuals, model building, coefficient of determination, selection of a subset of regressors.

Assessment

GS1 GRADING SCHEMA 1 Used for standard coursework units

Students please note: The marks and grades received by students on assessments may be subject to further moderation. All marks and grades are to be considered provisional until endorsed by the relevant School Progression Panel.

ON CAMPUS
TypeDescriptionValue
AssignmentAssignment on the implementation of statistical analysis40%
ReportReport on analysis of real data set40%
PresentationVideo presentation20%
ONLINE
TypeDescriptionValue
AssignmentAssignment on the implementation of statistical analysis40%
ReportReport on analysis of real data set40%
PresentationVideo presentation20%

Disability Standards for Education (Commonwealth 2005)

For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Access and Inclusion website.

Academic Misconduct

Edith Cowan University has firm rules governing academic misconduct and there are substantial penalties that can be applied to students who are found in breach of these rules. Academic misconduct includes, but is not limited to:

  • plagiarism;
  • unauthorised collaboration;
  • cheating in examinations;
  • theft of other students' work;

Additionally, any material submitted for assessment purposes must be work that has not been submitted previously, by any person, for any other unit at ECU or elsewhere.

The ECU rules and policies governing all academic activities, including misconduct, can be accessed through the ECU website.

MAT6104|1|2