R allows users to store data in objects that can be named and manipulated. Objects are created using <- and can contain vectors, matrices, or the output of functions. Functions take arguments as input and return output. Users can write their own functions to perform custom operations on data like randomly sampling values from a die vector.

1. R - Practice

2. > 1 + 1
[1] 2
-----------
> 100:130
[1] 100 101 102 103 104 105 106 107 108 109 110 111 112 [14] 113
114 115 116 117 118 119 120 121 122 123 124 125 [25] 126 127 128
129 130

3. Error
> 3 % 5
Error: unexpected input in "3 % 5“
------
If you type an incomplete command and press Enter, R will display a + prompt,
which means it is waiting for you to type the rest of your command. Either finish
the command or hit Escape to start over:
> 5 -
+
+
1
[1] 4

4. Objects
R lets you save data by storing it inside an R object.
What’s an object?
Just a name that you can use to call up stored data. For example, you
can save data into an object like a or b
a <- 1
a # output: 1
a + 2 # output : 3

5. Object creation
< followed by –
die <- 1:6
die # Output: 1 2 3 4 5 6
Rules for Object creation:
name an object in R almost anything you want, but there are a few rules.
First, a name cannot start with a number.
Second, a name cannot use some special symbols, like ^, !, $, @, +, -, /, or *

6. Case sensitive
• R also understands capitalization (or is case-sensitive), so name and
Name will refer to different objects:
Name <- 1
name <- 0
Name + 1 # Output: 2

7. List of Objects ls()
Find object names you have already used with the function using ls:
ls()
#Output: "a" "die" "my_number" "name" "Name"

8. die <- 1:6
die - 1 ## 0 1 2 3 4 5
die / 2 ## 0.5 1.0 1.5 2.0 2.5 3.0
die * die ## 1 4 9 16 25 36

9. die ## 1 2 3 4 5 6
die + 1:2 ## 2 4 4 6 6 8 - HOW?

10. R will repeat a short vector to do element-wise
operations with two vectors of uneven lengths

11. Warning
die + 1:4 ## 2 4 6 8 6 8
Warning message: In die + 1:4 : longer object length is not a multiple of
shorter object length

12. Creating Matrices For Multiplication
inner multiplication with the %*% operator
outer multiplication with the %o% operator

13. %*% - inner multiplication
die %*% die
Output: 91 - the output has been generated as a vector
die %o% die
Output:
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1 2 3 4 5 6
--the output has been generated as a matrix of one row and one column

16. Functions
R comes with many functions for tasks like random sampling.
round a number with the round function,
calculate its factorial with the factorial function.
round(3.1415)
## 3
factorial(3)
## 6

17. Functions with Arguments
 The data that you pass into the function is called the function’s argument.
 The argument can be raw data, an R object, or even the results of another R
function.
 R will work from the innermost function to the outermost
mean(1:6)
## 3.5
mean(die)
## 3.5
round(mean(die))
## 4

18. • simulate a roll of the die with R’s sample function
sample(x = 1:4, size = 2)
## 3 2
Try:
die=1:6
sample(x = die, size = 1)
sample(size = 1, x = die) ## output random sample between 1 to 6
two arguments: a vector named x and a number named size
Note: Many R functions take multiple arguments

19. Writing Your Own Functions
die <- 1:6
dice <- sample(die, size = 2, replace = TRUE)
sum(dice)