Extend your knowledge of linear regression to the situations where the response variable is binary, a count, or categorical as well as to hierarchical experimental set-up. Advanced Statistical Inference and Modelling Using R is part two of the Statistical Analysis in R professional certificate. This course is directed at people who are already familiar with basic linear regression and fundamentals of statistical inference. It extends the knowledge of linear regression to the situations where the response variable is binary, a count, or categorical as well as to hierarchical experimental set-up.
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While very practice oriented, it aims to give the students the understanding of why the method works (theory), how to implement it (programming using R) and when to apply it (and where to look if the particular method is not applicable in the specific situation).
This course is part of the Statistical Analysis in R Professional Certificate.
What you'll learn
- Exploratory data analysis and data visualisation using R.
- Multivariate analysis using Generalised Linear Models (GLMs):
- Binary response (logistic regression) GLM
- Poisson counts GLM
- Nominal categorical response (multinomial logistic GLM)
- Ordinal categorical response (ordinal logistic GLM)
- Mixed effects linear regression models. Structure, assumptions, diagnostics and interpretation. Model selection.
- Basics of power analysis (sample size evaluation) and some thoughts on experimental design and missing data.
