R

Statistica exercises

All the exerercises I've done in the third semester of university in the statistica course.

The exercises are ordered by date, some of them contains the part of the exercise of Izzo. Most of the exercises are made in R and some of them in XLSX to make easier my life.

R notes

Following the R manual.
For a point and click interface you need to use Rcmdr package.

Coding

To get help help(solve) or ?solve or help("[["), with the brakets to make it understanding that the brackets are not used as brackets. Help is also available in HTML version with help.start().
The double quote marks " are more used that the single one.
q() to quit an R session.
objects() or ls() to get objects present in memory. rm(r) after r <- 5 removes the object r.

x <- c(1,2,3) is a function to assign values to a vector. y <- c(x, 5, x); copies the vector x into y to create a vector of 7 elemets. It's possible to devide and multiply directly vector, for exaple:

x <- c(1.0,2,3);
y <- 2/x

[1] 2.0000000 1.0000000 0.6666667

In addition to normal operators (+ - * /) are available:

• log(numer, base) or log(number) for base e.
• exp() is e^x, for example exp(5) is e^5.
• sin()
• cos()
• tan()
• sqrt() can also work with complex numers e.g. sqrt(-17+0i)
• max and min() secect the biggest and smaller number of a vector

lenght() is the number of elements present in a vector.
mean() is the average, like sum(x)/length(x).
var() is sample variance (varianza di campionamento).
sort() return the vector sorted, there are also order() and sort.list() that produce something different.
pmin() and pmax() return a vector (of length equal to their longest argument) that contains in each element the largest (and smallest) element in that position in any of the input vectors.