Working with data and functions

Exploring the MLB data

Questions:

• How many observations are in the dataset?
• Who is the tallest / smallest player?
• Are players older than 32 significantly heavier than younger players?

t.test(weight ~ old,data = mlb)

    Welch Two Sample t-test

data:  weight by old
t = -3.9723, df = 396.06, p-value = 8.456e-05
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -8.567759 -2.894750
sample estimates:
mean in group FALSE  mean in group TRUE 
           200.4798            206.2110 

lapply / anonymous function: Who is the average size by position?

1. split the dataset by position to obtain a list
2. run mean on the list

lapply(by_pos,nrow)

$Catcher
[1] 76

$Designated_Hitter
[1] 18

$First_Baseman
[1] 55

$Outfielder
[1] 194

$Relief_Pitcher
[1] 315

$Second_Baseman
[1] 58

$Shortstop
[1] 52

$Starting_Pitcher
[1] 221

$Third_Baseman
[1] 45

A custom function: What’s the size of these players in centimeters?

inchToCm <- function(size_in_inch,meters = T,digits=2){
  out <- size_in_inch * 2.54
  if(meters) out <- round(out/100,digits=2)
  out
}
inchToCm(sizes)

          Catcher Designated_Hitter 
             1.85              1.89 
    First_Baseman        Outfielder 
             1.88              1.85 
   Relief_Pitcher    Second_Baseman 
             1.89              1.81 
        Shortstop  Starting_Pitcher 
             1.83              1.90 
    Third_Baseman 
             1.86