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Bio300b logistics
The who, what, where and when of Bio300b
Lecture 1: Data lifecycle
Following data from birth, trying to avoid data death in the data lifecycle.
Lecture 2: Using R
An introduction to using R.
Lecture 3: Data manipulation
Using the tidyverse to load, tidy and process data.
Lecture 4: Data visualisation
Using ggplot2 to make beautiful figures.
Lecture 5: Experimental design
Lecture 6: Descriptive statistics
Lecture 7: Linear regression
Correlations and linear regression with continuous and categorical predictors.
Lecture 8: Multiple linear regression
For models with more than one predictor, you need multiple regression.
Lecture 9: Generalised linear models
Got Poisson or binomial data? Use Generalised linear models.
Lecture 10: Mixed effect models
Clustered data? You need to use a mixed effect model.
Lecture 11: Survival Analysis
Do you data show the time or distance until event happens? Maybe you need survival analysis.