Computing With Data Using R (2019)

Files

• day01-01-possibilities.md
• day01-02-ggplot2.R
• day01-10-read_data.md
• day01-20-data_wrangling_intro.R
• day01-99-data_wrangling_intro-exercises.pdf
• day01-99-ggplot2-exercises.pdf
• day02-01-ggplot2-lines.R
• day02-03-data_wrangling-output.Rmd
• day02-04-data_cleaning.Rmd
• day02-05-reproducible_research.pdf
• day02-06-relational_data.Rmd
• day02-07-dbs.Rmd
• day02-20-datetime.Rmd
• day02-21-forcats.Rmd
• day02-22-stringr.Rmd
• day02-90-diamonds-exercises-solutions.pdf
• day02-90-diamonds-exercises.Rmd
• day03-01-working-examples-linear-models.Rmd
• day03-01-working-examples-linear-models.html
• day03-02-why-normal-19-eng.pdf
• day03-03-hypothesis-test-19-eng.pdf
• day03-cowidur.pdf
• day03-regression-exercise.Rmd
• day04-01-standard-errors-bootstrap-deltamethod.R
• day04-03-confidence-intervals.html
• day04-06-lm-ar1-error.html
• day04-11-r-basics.R
• day04-11-r-basics.html
• day04_t01_manymodels.html
• day04_t02_crossvalidation.html
• day04_t03_bootstrap.html
• day04_t04_exercises.html
• day04_t05_script.R
• day04_tvede.zip
• day05_aims_freq.csv
• day05_boys_names.csv
• day05_cluster_exercises.Rmd
• day05_cluster_exercises.html
• day05_clustering.Rmd
• day05_clustering.html
• day05_fig.zip
• day05_functional_programming.Rmd
• day05_parallelisation.Rmd
• day05_pca.Rmd
• day05_pca.html
• day06_classification.pdf
• day06_collinearity.R
• day06_crime.csv
• day06_glmnet.pdf
• day06_glmnet_R.Rmd
• day06_glmnet_R.html
• day06_hitters_solution.Rmd
• day06_lm_pn.R
• day06_logistic_regression.Rmd
• day06_logistic_regression.html
• day06_penalised_exercises.html
• day06_penalised_regression.pdf
• day06_randomForest.R
• day06_rpart.R
• multiplot.R