Visual Statistics Use R!

Foreword
I One or two dimensions
	The data
		Origin of the data
		Population and sample
		How to obtain the data
		What to find in the data
			Why do we need the data analysis
			What data analysis can do
			What data analysis cannot do
		Answers to exercises
	How to process the data
		General purpose software
		Statistical software
			Graphical systems
			Statistical environments
		The very short history of the S and R
		Use, advantages and disadvantages of the R
		How to download and install R
		How to start with R
			Launching R
			First steps
			How to type
			Overgrown calculator
			How to play with R
		R and data
			How to enter the data from within R
			How to name your objects
			How to load the text data
			How to load data from Internet
			How to use read.table() properly
			How to load binary data
			How to load data from clipboard
			How to edit data in R
			How to save the results
			History and scripts
		R graphics
			Graphical systems
			Graphical devices
			Graphical options
			Interactive graphics
		Answers to exercises
	Types of data
		Degrees, hours and kilometers: measurement data
		Grades and t-shirts: ranked data
		Colors, names and sexes: nominal data
			Character vectors
			Factors
			Logical vectors and binary data
		Fractions, counts and ranks: secondary data
		Missing data
		Outliers, and how to find them
		Changing data: basics of transformations
			How to tell the kind of data
		Inside R
			Matrices
			Lists
			Data frames
			Overview of data types and modes
		Answers to exercises
	One-dimensional data
		How to estimate general tendencies
			Median is the best
			Quartiles and quantiles
			Variation
		1-dimensional plots
		Confidence intervals
		Normality
		How to create your own functions
		How good is the proportion?
		Answers to exercises
	Two-dimensional data: differences
		What is a statistical test?
			Statistical hypotheses
			Statistical errors
		Is there a difference? Comparing two samples
			Two sample tests
			Effect sizes
		If there are more than two samples: ANOVA
			One way
			More then one way
		Is there an association? Analysis of tables
			Contingency tables
			Table tests
		Answers to exercises
			Exercises on two samples
			Exercises on ANOVA
			Exercises on tables
	Two-dimensional data: models
		Analysis of correlation
			Plot it first
			Correlation
		Analysis of regression
			Single line
			Many lines
			More then one way, again
		Probability of the success: logistic regression
		Answers to exercises
			Correlation and linear models
			Logistic regression
		How to choose the right method
II Many dimensions
	Draw
		Pictographs
		Grouped plots
		3D plots
	Discover
		Discovery with primary data
			Shadows of hyper clouds: PCA
			Correspondence
			Projections, unfolds, t-SNE and UMAP
			Non-negative matrix factorization
		Discovery with distances
			Distances
			Making maps: multidimensional scaling
			Making trees: hierarchical clustering
			How to know the best clustering method
			How to compare clusterings
			How good are resulted clusters
			Making groups: k-means and friends
			How to know cluster numbers
			Use projection pursuit for clustering
			How to compare different ordinations
		Answers to exercises
	Learn
		Learning with regression
			Linear discriminant analysis
			Recursive partitioning
		Ensemble learnig
			Random Forest
			Gradient boosting
		Learning with proximity
		Learning with rules
		Learning from the black boxes
			Support Vector Machines
			Neural Networks
		Semi-supervised learning
		How to choose the right method
		Answers to exercises
Appendices
	Example of R session
		Starting...
		Describing...
		Plotting...
		Testing...
		Finishing...
		Answers to exercises
	Ten Years Later, or use R script
		How to make your R script
		My R script does not work!
		Common pitfalls in R scripting
			Advices
				Use the Source, Luke!..
				Keep it simple
				Learn to love errors and warnings
				Subselect by names, not numbers
				About reserved words, again
			The Case-book of Advanced R user
				A Case of Were-objects
				A Case of Missing Compare
				A Case of Outlaw Parameters
				A Case of Identity
				The Adventure of the Floating Point
				A Case of Twin Files
				A Case of Bad Grammar
				A Case of Double Dipping
				A Case of Factor Join
				A Case of Bad Font
				A Case of Disproportionate Condition
			Good, Bad, and Not-too-bad
				Good
				Bad
				Not too bad
		Answers to exercises
	R fragments
		R and databases
		R and time
		R and bootstrap
		R and shape
		R and Bayes
		R, DNA and evolution
		R and reporting
		R without graphics
		Answers to exercises
	Most essential R commands
	The short R glossary
	References
	Reference card