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3 course outlines found

1

BIOSCI 738

: Advanced Biological Data Analysis
2022 Semester One (1223)
Building on a strong foundation in quantitative biology, fundamental statistical methods and basic R programming, students will learn an array of advanced biostatistical methods for data analysis. Topics covered include: data wrangling, methods for the analysis of designed experiments, regression analysis, including mixed effect models, and the analysis of multivariate data, including advanced supervised and unsupervised learning techniques. Requires students to apply their knowledge across a myriad of complex biological datasets.
Subject: Biological Sciences
No pre-requisites or restrictions
2

BIOSCI 738

: Advanced Biological Data Analysis
2021 Semester One (1213)
Design and analysis of experiments for both field and bench scientists. Methods for the analysis of designed experiments, including analysis of variance with fixed, random and mixed effects; also, regression analysis and analysis of covariance. Methods for the analysis of multivariate datasets such as cluster analysis, principal components analysis, multidimensional scaling, and randomisation methods. There will be a practical component to this course involving the use of appropriate statistical software.
Subject: Biological Sciences
No pre-requisites or restrictions
3

BIOSCI 738

: Advanced Biological Data Analysis
2020 Semester One (1203)
Design and analysis of experiments for both field and bench scientists. Methods for the analysis of designed experiments, including analysis of variance with fixed, random and mixed effects; also, regression analysis and analysis of covariance. Methods for the analysis of multivariate datasets such as cluster analysis, principal components analysis, multidimensional scaling, and randomisation methods. There will be a practical component to this course involving the use of appropriate statistical software.
Subject: Biological Sciences
Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208, or equivalent