Using real-world examples drawn from modern society (e.g. social media; news and government outlets etc.) and the fields of biology, medicine, ecology, and environmental sciences, this unit will help students learn to rigorously analyze and critically evaluate statistics and data visualizations. Students will develop an understanding of robust study designs and testing hypotheses using models and implementing modern statistical and data visualization tools. They will become proficient in the application of the freely available software R and R studio, for basic graphical and statistical data analyses. The unit extends ANOVA and linear regression to focus on General Linear Models and Generalized Linear Models. Students will be introduced to multivariate methods, likelihood and the concepts and pitfalls of frequentist and Bayesian statistics. Skills to interpret and critically evaluate real world data are readily transferrable to many science, management, engineering, information technology and health fields.
It is assumed that prior to enrolment, students will have basic knowledge of study design principles (e.g. randomised sampling, replication, independence, etc.) and statistics (e.g. mean, standard error, ANOVA, simple linear regression) with previous experience using R or R Studio or other computer-based statistical software.
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