Here are all the sklls lab materials
In this first session, we’ll get reacquainted with R
and learn some tips to make working in RStudio more accessible - and colourful! We’ll also revise some core concepts around reading in and working with data in a tidy way.
Building on last week’s foundations, we’ll explore how to present data in a clean, professional, and easy-to-read way, using nicely formatted summary tables and powerful data visualisation tools.
Thus far all the data we’ve seen has been nicely cleaned and ready to use - but that’s hardly ever the case! This time through we’ll tackle difficult data, and discuss deciding what to do when your data is deficient or disordered.
Our one-letter-per-week theme continues, with this week’s spotlight on the letter t! We look at means plots and t-tests in R
- and look ahead to the upcoming take-away paper assessment.
We will work through the key parts of the first sample TAP, with time to answer your questions about the sample TAP and next week’s real TAP assessment.
This week we will open a big chapter on the Linear Model. We will learn how to fit and interpret a basic one-predictor model and how to visualise it on a scatterplot.
Building on last weeks’s Skills lab, we look at the statistical testing of linear model coefficients and assess the overall fit of the model.
Like tibbles, our predictors are multiplying! We’ll demo how to add predictors to the linear model, and how to interpret the more complex model once you do.
lm()
recap and what nextIn the final Skills lab we go over the functions that we’ve used to fit and evaluate linear models, we learn how to simulate simple data, and have a taste of some advanced R
.