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* hello world
Start the R interpreter and print the string "hello world"
* function
Create a function called that does what you did manually
in the previous exercise. 
* create an anonymous version of the same function
* use Google to figure out what R's rules are for naming variables and functions
* hello(name) function
Create a variant of the previous function that accepts a `name`
parameter and prints "Hello Mary", "Hello Lamb", etc. 

Hint: you'll need to figure out how to concatenate/join strings
* hello(name) with a default argument
Give the `name` argument a default value.
* create a `vector` of the following strings and assign it to a variable
"Mary", "had", "a", "little", "lamb"
* use to find a function that can convert each element in that vector to uppercase 
* find a function that will give you the length of the vector
* figure out the syntax to get the third element in the vector
* create a function that applies another function to each element in a vector
* find a function that will create a sequence of integers
This is like the `range` function in Python.
* use that function and the `matrix` function to create a 4 x 5 matrix of the first 20 natural numbers
* figure out the syntax to get the matrix element at row 2, col 3
* multiply every element in the matrix by 3 
* find a function that gives you the dimensions of the matrix
* convert this matrix to a vector
* create a Boolean matrix of the same size 
... that indicates whether the elements in our first matrix are > 13
* use the Boolean matrix to take a subset of our first matrix
... where the condition is true
... and where it is false
* what is the type of the subset
* figure out how to create a random sample of 100 integers
* take a random sample of five elements from your first matrix
* find the built-in dataset `swiss` and the help information about it
* what are the `type`, `dimensions`, `structure`, and `dimension names` of this dataset
* figure out how to access each column of this dataset individually
* show the first and last six elements of this dataset
hint: there are built in functions that will do this for you