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Showing 25 course outlines from 3697 matches

2876

STATS 763

: Advanced Regression Methodology
2020 Semester One (1203)
Generalised linear models, generalised additive models, survival analysis. Smoothing and semiparametric regression. Marginal and conditional models for correlated data. Model selection for prediction and for control of confounding. Model criticism and testing. Computational methods for model fitting, including Bayesian approaches.
Subject: Statistics
No pre-requisites or restrictions
2877

STATS 765

: Statistical Learning for Data Science
2024 Semester One (1243)
Concepts of modern predictive modelling and machine learning such as loss functions, overfitting, generalisation, regularisation, sparsity. Techniques including regression, recursive partitioning, boosting, neural networks. Application to real data sets from a variety of sources, including data quality assessment, data preparation and reporting.
Subject: Statistics
Prerequisite: 15 points from ENGSCI 314, STATS 201, 207, 208 and 15 points from STATS 210, 225, 707 Corequisite: May be taken with STATS 707
Restriction: STATS 369
2878

STATS 765

: Statistical Learning for Data Science
2023 Semester One (1233)
Concepts of modern predictive modelling and machine learning such as loss functions, overfitting, generalisation, regularisation, sparsity. Techniques including regression, recursive partitioning, boosting, neural networks. Application to real data sets from a variety of sources, including data quality assessment, data preparation and reporting.
Subject: Statistics
Prerequisite: 15 points from STATS 201 or 207 or 208 and 15 points from STATS 210 or 225, or STATS 707 Corequisite: May be taken with STATS 707
Restriction: STATS 369
2879

STATS 765

: Statistical Learning for Data Science
2022 Semester One (1223)
Concepts of modern predictive modelling and machine learning such as loss functions, overfitting, generalisation, regularisation, sparsity. Techniques including regression, recursive partitioning, boosting, neural networks. Application to real data sets from a variety of sources, including data quality assessment, data preparation and reporting.
Subject: Statistics
Prerequisite: 15 points from STATS 201 or 207 or 208 and 15 points from STATS 210 or 225, or STATS 707 Corequisite: May be taken with STATS 707
Restriction: STATS 369
2880

STATS 765

: Statistical Learning for Data Science
2021 Semester One (1213)
Concepts of modern predictive modelling and machine learning such as loss functions, overfitting, generalisation, regularisation, sparsity. Techniques including regression, recursive partitioning, boosting, neural networks. Application to real data sets from a variety of sources, including data quality assessment, data preparation and reporting.
Subject: Statistics
Prerequisite: 15 points from STATS 201 or 207 or 208 and 15 points from STATS 210 or 225, or STATS 707 Corequisite: May be taken with STATS 707
Restriction: STATS 369
2881

STATS 765

: Statistical Learning for Data Science
2020 Semester One (1203)
Concepts of modern predictive modelling and machine learning such as loss functions, overfitting, generalisation, regularisation, sparsity. Techniques including regression, recursive partitioning, boosting, neural networks. Application to real data sets from a variety of sources, including data quality assessment, data preparation and reporting.
Subject: Statistics
Prerequisite: 15 points from STATS 201 or 207 or 208 and 15 points from STATS 210 or 225, or STATS 707 Corequisite: May be taken with STATS 707
Restriction: STATS 369
2882

STATS 766

: Multivariate Analysis
2023 Semester Two (1235)
A selection of topics from multivariate analysis, including: advanced methods of data display (e.g., Correspondence and Canonical Correspondence Analysis, Biplots, and PREFMAP) and an introduction to classification methods (e.g., various types of Discriminant Function Analysis).
Subject: Statistics
Prerequisite: STATS 310 or 732
2883

STATS 766

: Multivariate Analysis
2022 Semester Two (1225)
A selection of topics from multivariate analysis, including: advanced methods of data display (e.g., Correspondence and Canonical Correspondence Analysis, Biplots, and PREFMAP) and an introduction to classification methods (e.g., various types of Discriminant Function Analysis).
Subject: Statistics
Prerequisite: STATS 302 or 767
2884

STATS 767

: Foundations of Applied Multivariate Analysis
2024 Semester One (1243)
Fundamentals of exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Subject: Statistics
Prerequisite: 15 points from ENGSCI 314, STATS 201, 207, 208, 707
Restriction: STATS 302
2885

STATS 767

: Foundations of Applied Multivariate Analysis
2023 Semester One (1233)
Fundamentals of exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208, 707
Restriction: STATS 302
2886

STATS 767

: Foundations of Applied Multivariate Analysis
2022 Semester One (1223)
Fundamentals of exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208, 707
Restriction: STATS 302
2887

STATS 767

: Foundations of Applied Multivariate Analysis
2021 Semester One (1213)
Fundamentals of exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208, 707
Restriction: STATS 302
2888

STATS 767

: Foundations of Applied Multivariate Analysis
2020 Semester One (1203)
Fundamentals of exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208
Restriction: STATS 302
2889

STATS 768

: Longitudinal Data Analysis
2024 Semester Two (1245)
Exploration and regression modelling of longitudinal and clustered data, especially in the health sciences: mixed models, marginal models, dropout, causal inference.
Subject: Statistics
Prerequisite: 15 points from ENGSCI 314, STATS 201, 207, 208, 210, 707
2890

STATS 768

: Longitudinal Data Analysis
2023 Semester Two (1235)
Exploration and regression modelling of longitudinal and clustered data, especially in the health sciences: mixed models, marginal models, dropout, causal inference.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208, 210, 707
2891

STATS 768

: Longitudinal Data Analysis
2021 Semester Two (1215)
Exploration and regression modelling of longitudinal and clustered data, especially in the health sciences: mixed models, marginal models, dropout, causal inference.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208, 210, 707
2892

STATS 768

: Longitudinal Data Analysis
2020 Semester Two (1205)
Exploration and regression modelling of longitudinal and clustered data, especially in the health sciences: mixed models, marginal models, dropout, causal inference.
Subject: Statistics
No pre-requisites or restrictions
2893

STATS 769

: Advanced Data Science Practice
2024 Semester Two (1245)
Databases, SQL, scripting, distributed computation, other data technologies.
Subject: Statistics
Prerequisite: 15 points from STATS 220, 369, 380 and 15 points from ENGSCI 314, STATS 201, 207, 208, 707
2894

STATS 769

: Advanced Data Science Practice
2023 Semester Two (1235)
Databases, SQL, scripting, distributed computation, other data technologies.
Subject: Statistics
Prerequisite: 15 points from STATS 220, 369, 380 and 15 points from BIOSCI 209, STATS 201, 207, 208, 707
2895

STATS 769

: Advanced Data Science Practice
2022 Semester Two (1225)
Databases, SQL, scripting, distributed computation, other data technologies.
Subject: Statistics
Prerequisite: 15 points from STATS 220, 369, 380 and 15 points from BIOSCI 209, STATS 201, 207, 208, 707
2896

STATS 769

: Advanced Data Science Practice
2021 Semester Two (1215)
Databases, SQL, scripting, distributed computation, other data technologies.
Subject: Statistics
Prerequisite: 15 points from STATS 220, 369, 380 and 15 points from BIOSCI 209, STATS 201, 207, 208, 707
2897

STATS 769

: Advanced Data Science Practice
2020 Semester Two (1205)
Databases, SQL, scripting, distributed computation, other data technologies.
Subject: Statistics
No pre-requisites or restrictions
2898

STATS 770

: Introduction to Medical Statistics
2024 Semester One (1243)
An introduction to ideas of importance in medical statistics, such as measures of risk, basic types of medical study, causation, ethical issues and censoring, together with a review of common methodologies.
Subject: Statistics
Prerequisite: 15 points from ENGSCI 314, STATS 201, 207, 208 and 15 points from STATS 210, 225, 707
2899

STATS 770

: Introduction to Medical Statistics
2023 Semester One (1233)
An introduction to ideas of importance in medical statistics, such as measures of risk, basic types of medical study, causation, ethical issues and censoring, together with a review of common methodologies.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208 and 15 points from STATS 210, 225, 707
2900

STATS 770

: Introduction to Medical Statistics
2022 Semester Two (1225)
An introduction to ideas of importance in medical statistics, such as measures of risk, basic types of medical study, causation, ethical issues and censoring, together with a review of common methodologies.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208 and 15 points from STATS 210, 225, 707