1. Introduction to R and Statistics Thomas INGICCO G. Courbet, Le désespéré (Autoportrait) G. Courbet, The desperate man (Self-portrait)

2. R is a freeware…

3. … but before all it is a language with its own grammar made of:

4. To create an object which will contain data or informations, we use "<-" : aa <- NULL aa <- "A sentence" bb <- 10:34 cc <- matrix(10:34, nc=5, nr=5) To see the content of the object, we type its name: aa Hash symbol (#) allows you to comment your script: aa # This is a comment Semicolon allows you to separate the commands on the same line: aa ; bb ; cc # We look at the content of the three objects R is case sensitive aa Aa # R being a language, when you make a mistake, it tells you Spaces are not important bbb<-10 : 34

5. … but R is also a calculator: 25/5 5^2 25^0.5 sqrt(25) # This is a function sqrt ?sqrt help(sqrt)

6. … but R is also a calculator: 25/5 5^2 25^0.5 sqrt(25) # This is a function sqrt ?sqrt help(sqrt) sqrt(sum(bb)) # Functions are matriochkas

7. … but R is also a calculator: 25/5 5^2 25^0.5 sqrt(25) # This is a function sqrt ?sqrt help(sqrt) sqrt(sum(bb)) # Functions are matriochkas bb[-3] bb+bb bb+bb[-3] bb+cc

8. … but before all it is a language with its own grammar made of:

9. Modes – nature of your data - Numeric – numbers (51, 32, 47mm) -Character – chain of characters (« y », « a+b+c ») -Factor – qualitative values (« Red », « Orange ») -Logical – specific attributes (TRUE, FALSE, NA) Special arguments - NA – Not Available, absence of data -NULL – Empty object -TRUE or T – Logical argument -FALSE or F– Logical argument … but before all it is a language with its own grammar made of:

10. Classes – how you present your data - Vector – series of values of 1 dimension -Matrix – series of values of 2 dimensions -Arrays – series of values of n dimensions -Data Frame – series of values in columns -List – series of objects -Table – Contingency table … but before all it is a language with its own grammar made of: ls() # Check the list of the created objects # Vector is.vector(bb)

11. Classes – how you present your data - Vector – series of values of 1 dimension -Matrix – series of values of 2 dimensions -Arrays – series of values of n dimensions -Data Frame – series of values in columns -List – series of objects -Table – Contingency table … but before all it is a language with its own grammar made of: # Matrix class(cc) cc <- matrix(10:34, nc=5, nr=5) # Remember ccc <- c(10:34) ccc

12. Classes – how you present your data - Vector – series of values of 1 dimension -Matrix – series of values of 2 dimensions -Arrays – series of values of n dimensions -Data Frame – series of values in columns -List – series of objects -Table – Contingency table … but before all it is a language with its own grammar made of: # Matrix class(cc) cc <- matrix(10:34, nc=5, nr=5) # Remember ccc <- c(10:34) ccc is.vector(ccc) dim(ccc)<-c(5,5) ccc

13. Classes – how you present your data - Vector – series of values of 1 dimension -Matrix – series of values of 2 dimensions -Arrays – series of values of n dimensions -Data Frame – series of values in columns -List – series of objects -Table – Contingency table … but before all it is a language with its own grammar made of: # Matrix class(cc) cc <- matrix(10:34, nc=5, nr=5) # Remember ccc <- c(10:34) ccc is.vector(ccc) dim(ccc)<-c(5,5) ccc is.matrix(ccc)

14. Classes – how you present your data - Vector – series of values of 1 dimension -Matrix – series of values of 2 dimensions -Arrays – series of values of n dimensions -Data Frame – series of values in columns -List – series of objects -Table – Contingency table … but before all it is a language with its own grammar made of: # Matrix class(cc) cc <- matrix(10:34, nc=5, nr=5) # Remember ccc <- c(10:34) ccc is.vector(ccc) dim(ccc)<-c(5,5) ccc is.matrix(ccc) matrix(1:6, 3, 2) matrix(1:6, 3, 2, byrow=T)

15. Classes – how you present your data - Vector – series of values of 1 dimension -Matrix – series of values of 2 dimensions -Arrays – series of values of n dimensions -Data Frame – series of values in columns -List – series of objects -Table – Contingency table … but before all it is a language with its own grammar made of: # Data.frame dd<-read.table("K:/Cours/Philippines/Statistics-210/Lecture-4/Ceramics.txt", header=TRUE) # Opening Data; return is possible in a function; a function has arguments class(dd) dd$Type dd[,9] dd[3,8:11]