Activity 4

# Addition
2+3

[1] 5

# Division
2/3

[1] 0.6666667

# Exponentiation
2^3 

[1] 8

# Square root
sqrt(2)

[1] 1.414214

# Logarithms
log(2)

[1] 0.6931472

Question 1: Compute the log base 5 of 10 and the log of 10

log10(5)

[1] 0.69897

log(10)

[1] 2.302585

Computing some offensive metrics in Baseball

#Batting Average=(No. of Hits)/(No. of At Bats)
#What is the batting average of a player that bats 29 hits in 112 at bats?
BA=(29)/(112)
BA

[1] 0.2589286

Batting_Average=round(BA,digits = 3)
Batting_Average

[1] 0.259

Question 2: What is the batting average of a player that bats 42 hits in 212 at bats?

#On Base Percentage
#OBP=(H+BB+HBP)/(At Bats+BB+HBP+SF)
#Let us compute the OBP for a player with the following general stats
#AB=515,H=172,BB=84,HBP=5,SF=6
OBP=(172+84+5)/(515+84+5+6)
OBP

[1] 0.4278689

On_Base_Percentage=round(OBP,digits = 3)
On_Base_Percentage

[1] 0.428

Often you will want to test whether something is less than, greater than or equal to something.

#Question_3:Compute the OBP for a player with the following general stats:
#AB=565,H=156,BB=65,HBP=3,SF=7
#OBP=(H+BB+HBP)/(AT Bats+BB=HBP+SF)
OBP = (156+65+3)/(565+65+3+7)
On_Base_Percentage=round(OBP,digits = 3)
On_Base_Percentage

[1] 0.35

# Combination of statements
2 < 3 | 1 == 5 # 2<3 is True, 1==5 is False, True OR False is True

[1] TRUE

Total_Bases <- 6 + 5
Total_Bases*3

[1] 33

ls()

[1] "BA"                 "Batting_Average"    "OBP"               
[4] "On_Base_Percentage" "Total_Bases"       

rm(Total_Bases)

Vector

pitches_by_innings <- c(12, 15, 10, 20, 10) 
pitches_by_innings

[1] 12 15 10 20 10

strikes_by_innings <- c(9, 12, 6, 14, 9)
strikes_by_innings

[1]  9 12  6 14  9

#Question_4: Define two vectors,runs_per_9innings and hits_per_9innings, each with five elements. 
runs_per_9inning<-c(2,5,7,11,13)
hits_per_9innings<-c(11,13,16,18,19)
runs_per_9inning

[1]  2  5  7 11 13

hits_per_9innings

[1] 11 13 16 18 19

# replicate function
rep(2, 5)

[1] 2 2 2 2 2

# consecutive numbers
1:5

[1] 1 2 3 4 5

2:10

[1]  2  3  4  5  6  7  8  9 10

# sequence from 1 to 10 with a step of 2
seq(1, 20, by=3)

[1]  1  4  7 10 13 16 19

# add vectors
pitches_by_innings+strikes_by_innings

[1] 21 27 16 34 19

# compare vectors
pitches_by_innings == strikes_by_innings

[1] FALSE FALSE FALSE FALSE FALSE

# find length of vector
length(pitches_by_innings)

[1] 5

# find average value in vector
mean(pitches_by_innings)

[1] 13.4

pitches_by_innings

[1] 12 15 10 20 10

# If you want to get the first element:
pitches_by_innings[1]

[1] 12

#Question_5: Get the first element of hits_per_9innings.
pitches_by_innings[length(pitches_by_innings)]

[1] 10

#Question_6: Get the last element of hits_per_9innings.
pitches_by_innings[c(2, 3, 4)]

[1] 15 10 20

player_positions <- c("catcher", "pitcher", "infielders", "outfielders")

data.frame(bonus = c(2, 3, 1),#in millions 
           active_roster = c("yes", "no", "yes"), 
           salary = c(1.5, 2.5, 1))#in millions 

sample(1:10, size=5)

[1] 5 4 7 6 1

bar <- data.frame(var1 = LETTERS[1:10], var2 = 1:10)
# Check data frame
bar

n <- 5