Computing With Data Using R (2018)

Course plan

Below is the intended course plan (deviations to be expected).

Preparation

Before the first lecture, please pay attention to our preparation page.

First week

Mon 19 Feb Tue 20 Feb Wed 21 Feb
MORNING
 R101
RStudio
?function 		Distributions
Probability
t.test		 Rmarkdown
Summarising data Linear models and inference
Hypothesis testing
Confidence intervals
Non-parametric bootstrap 		More about linear models
AFTERNOON
 Linear models and lm
Dummy variables (factor)
Predictions from linear models 		Data wrangling
ggplot2 		Linear models and caveats
Collinearity in data
ggplot2 forcats
lubridate 		Between weeks exercise

Between weeks exercise

Hand-in by Sunday February 25 at 23:59 to {sorenh, tvede}asd@math.aau.dk subject "COWIDUR2018". Please send Rmd file (and possibly html/pdf). Can be done in groups of 1-3 individuals. Please include the name of the group members in the mail.

Last week

Wed 28 Feb Thur 1 Mar Fri 2 Mar
MORNING
 Discussion of exercise Relational data (joins)
extract/separate 		TBA
(e.g. broom)
Clustering e.g.
K-means
Hierarchical clustering
(soft clustering) 		k-fold cross-validation
Discriminant Analysis:
LDA and QDA 		Penalised/regularised regression:
LASSO and Ridge regression
Elastic Net and glmnet
AFTERNOON
 Random vectors
Whitening of data
Principal Components Analysis
Principal Component Regression 		Classification Trees (CART)
Random Forest 		Logistic regression
Handling strings in R (stringr) Splitting data and mapping (purrr) Interfacing with other languages
E.g. C++ using Rcpp
Final exercise

asta.math.aau.dk