7 R as a Calculator
R functions as a calculator.
5 + 2 # addition
[1] 7
5 - 2 # subtraction
[1] 3
5 * 2 # multiplication
[1] 10
5 / 2 # division
[1] 2.5
5 ^ 2 # exponentiation
[1] 25
5 %/% 2 # integer division
[1] 2
5 %% 2 # modulo (remainder after integer division)
[1] 1
abs(-5) # absolute value
[1] 5
sqrt(5) # square root
[1] 2.236068
log(5) # natural log
[1] 1.609438
More complex operations can be performed by using multiple mathematical operators and parentheses:
abs(5 - sqrt(2) * (5 ^ (5/2) - 2))
[1] 71.22851
Objects can be uses in calculations, too. Here we assign the value 5 to x
and then add 2 to it.
x <- 5
x + 2
[1] 7
Note that x
retains its original value of 5 since we did not reassign the result to x
.
x
[1] 5
To update x
with the result of x + 2
, assign it to x
:
x <- x + 2
x
[1] 7
When we perform a calculation in R (or any other operation, such as loading datasets or fitting models), results are stored in the intermediate object .Last.value
. We can access .Last.value
to perform multi-step calculations. We can calculate the standard error of the mpg
column in the mtcars
dataset as the standard deviation (sd
) divided by the square root of the sample size (n
):
n <- length(mtcars$mpg) # number of observations
sd(mtcars$mpg) # standard deviation
[1] 6.026948
.Last.value / sqrt(n) # standard error
[1] 1.065424
These examples of R’s utility as a calculator have all used individual numbers, also called scalars. These operations become more useful when we begin to work with numeric vectors and columns in dataframes.