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Showing 25 course outlines from 9861 matches

7876

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
7877

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
7878

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
7879

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
7880

STATS 767

: Foundations of Applied Multivariate Analysis
2025 Semester One (1253)
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
7881

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
7882

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
7883

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
7884

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
7885

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
7886

STATS 770

: Introduction to Medical Statistics
2025 Semester One (1253)
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
7887

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
7888

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
7889

STATS 770

: Introduction to Medical Statistics
2020 Semester One (1203)
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
No pre-requisites or restrictions
7890

STATS 773

: Design and Analysis of Clinical Trials
2025 Semester One (1253)
The theory and practice of clinical trials, including: design issues, data management, common analysis methodologies, intention to treat, compliance, interim analyses and ethical considerations.
Subject: Statistics
Prerequisite: 15 points from ENGSCI 314, STATS 201, 207, 208, 707
7891

STATS 776

: Estimating Animal Abundance
2025 Semester One (1253)
Fundamentals of the statistical methods that underly capture-recapture, distance sampling and occupancy analysis, focusing on the critical role that p, the probability of detection, plays in estimating n, the number of animals, or psi, the probability of species presence. Extensions to these fundamental tools including spatially explicit, genetic, and hierarchical methods will be covered.
Subject: Statistics
Prerequisite: 15 points from ENGSCI 314, STATS 201, 207, 208, 707
7892

STATS 776

: Estimating Animal Abundance
2024 Semester One (1243)
Fundamentals of the statistical methods that underly capture-recapture, distance sampling and occupancy analysis, focusing on the critical role that p, the probability of detection, plays in estimating n, the number of animals, or psi, the probability of species presence. Extensions to these fundamental tools including spatially explicit, genetic, and hierarchical methods will be covered.
Subject: Statistics
Prerequisite: 15 points from ENGSCI 314, STATS 201, 207, 208, 707
7893

STATS 776

: Estimating Animal Abundance
2023 Semester One (1233)
Fundamentals of the statistical methods that underly capture-recapture, distance sampling and occupancy analysis, focusing on the critical role that p, the probability of detection, plays in estimating n, the number of animals, or psi, the probability of species presence. Extensions to these fundamental tools including spatially explicit, genetic, and hierarchical methods will be covered.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208, 707
7894

STATS 776

: Estimating Animal Abundance
2022 Semester One (1223)
Fundamentals of the statistical methods that underly capture-recapture, distance sampling and occupancy analysis, focusing on the critical role that p, the probability of detection, plays in estimating n, the number of animals, or psi, the probability of species presence. Extensions to these fundamental tools including spatially explicit, genetic, and hierarchical methods will be covered.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208, 707
7895

STATS 776

: Estimating Animal Abundance
2021 Semester One (1213)
Fundamentals of the statistical methods that underly capture-recapture, distance sampling and occupancy analysis, focusing on the critical role that p, the probability of detection, plays in estimating n, the number of animals, or psi, the probability of species presence. Extensions to these fundamental tools including spatially explicit, genetic, and hierarchical methods will be covered.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208, 707
7896

STATS 776

: Topics in Environmental and Ecological Statistics
2020 Semester One (1203)
Subject: Statistics
No pre-requisites or restrictions
7897

STATS 779

: Professional Skills for Statisticians
2025 Semester One (1253)
Statistical software, data management, data integrity, data transfer, file processing, symbolic manipulation, document design and presentation, oral presentation, professional ethics.
Subject: Statistics
Prerequisite: 15 points from ENGSCI 314, STATS 201, 208, 707
7898

STATS 779

: Professional Skills for Statisticians
2024 Semester One (1243)
Statistical software, data management, data integrity, data transfer, file processing, symbolic manipulation, document design and presentation, oral presentation, professional ethics.
Subject: Statistics
Prerequisite: 15 points from ENGSCI 314, STATS 201, 208, 707
7899

STATS 779

: Professional Skills for Statisticians
2023 Semester One (1233)
Statistical software, data management, data integrity, data transfer, file processing, symbolic manipulation, document design and presentation, oral presentation, professional ethics.
Subject: Statistics
Prerequisite: STATS 201 or 208
7900

STATS 779

: Professional Skills for Statisticians
2022 Semester One (1223)
Statistical software, data management, data integrity, data transfer, file processing, symbolic manipulation, document design and presentation, oral presentation, professional ethics.
Subject: Statistics
No pre-requisites or restrictions