Learning Objectives

• What Is A Vector?
• How To Make One
• How To Delete One
• Vector Indexing (How To Subset)
• Work With Two Vectors
• Apply Functions To A Vector

What is a vector?

• Congrats, you have already worked with vectors!
  • (We forgot to tell you)
• Understanding vectors is CRITICAL to becoming a useR

## This is a vector, length == 1.
captain <- "John Smith"

## This is a vector, length == 2.
captain <- c("John", "Smith")

## This is a vector too, length == 5.
age <- c(22, 38, 26, 35, 35)

## What does c stand for?
?c
    

Combine

• Use the function c() to combine things
• Works for numerics, characters, booleans, dates, etc.
• All arguments are coerced to a common type
• Each vector is an object
  • (Everything is an object in R)

Your Turn!

## You can copy/paste this from the slide.
## These will be used again, don't delete.
age <- c(22,38,26,35,35,NA,54,2,27,14)
gender <- c("male","female","female","female","male",
            "male","male","male","female","female")

## Check that you have them with this code:
length(age)
length(gender)
    

The answer to both length() commands should be 10

STOP!

If you didn't succeed with the last slide, SAY SOMETHING!

Visualize A Vector

A vector is like a column in Excel

Note: NA isn't a string, it is NA

Apply A Function

• Some functions act on each element in the vector
• Some functions act on the vector in total

## Per Item
age + 1
            

[1] 23 39 27 36 36 NA 55  3 28 15
            

## In Total
table(gender)
            

gender
female   male 
     5      5 
            

NA

• NA is the bane of our existence
• na.rm = TRUE is our friend
• Example: mean()

## This will not work.
mean(age)
            

[1] NA

## Yeah, that's not right.
            

## This works just fine.
mean(age, na.rm = TRUE)
            

[1] 28.11111

## That's more like it.
            

HELP!

(You might need a tugboat)

• ?foo
• Code Completion
• RStudio help window
• Stack Overflow
• Google: Pre-pend search query with "R"
• Quick-R (Stat Methods)
• RStudio Cheatsheets

Note the lack of smoke coming from stack #4

Some Functions

Your Turn!

## Take a few minutes and spend some
## time using a few of these functions.
## Remember ? to get help with how to use the function.
    

Index[1]

• AKA Subsetting / Filtering
• Let's do this together

## Use the square bracket operator to select which
## entries in a vector to return.
## Remember: There are 10 entries in age and gender.

## But maybe we only want one of them.
gender[10]

## Or maybe we only want some of them.
age[3:5]
    

Index[2]

STOP ME IF THIS DOESN'T MAKE SENSE!

## Perhaps we only want to return the males.
gender[gender == "male"]

## More usefully - this works across vectors.
age[gender == "male"]
    

Visualize 2 Vectors

In this case, these vectors are in the same order . . .

Index[3]

## Make a new variable
age_of_men <- age[gender == "male"]

## Or use it in a function
mean( age[gender=="female"] )
    

Your Turn!

## Using the following Boolean Object
survived <- c(FALSE,TRUE,TRUE,TRUE,FALSE,
              FALSE,FALSE,FALSE,TRUE,TRUE)

## How many men survived the sinking of the Titanic?
## How many women?
    

Answer on the next slide!

Your Turn!

## How many men survived the sinking of the Titanic?
survived_men <- survived[gender=="male"]
table(survived_men)

## Extra credit for anyone who did it this way.
sum(survived_men)


## Try this to better understand.
survived_men == 1
    

Actual Passengers

Statistical Testing

• Statistical tests are functions in R:
  • Student's T-Test: t.test()
  • Chi Square Test: chisq.test()
• You know everything you need to know to run

Statistical Testing

t.test(age[gender=="male"], age[gender=="female"])
    

Welch Two Sample t-test

data:  age[gender == "male"] and age[gender == "female"]
t = 0.021341, df = 3.8789, p-value = 0.984
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -32.67896  33.17896
sample estimates:
mean of x mean of y 
    28.25     28.00 
    

One More Data Type

• Factor
• Superficially, similar to a string character
• More efficient with memory usage
• Defines a variable explicitly as a categorical

Make A Factor

gender
[1] "male"   "female" "female" "female" "male"   "male"   "male"   "male"  
 [9] "female" "female"
        

as.factor(gender)
 [1] male   female female female male   male   male   male   female female
Levels: female male
        

Take A Break!

Titanic in Cobh Harbour, County Cork Ireland