R Notebook Activity 4

4+3
4-3
4==3
3^2
sqrt(4)

Does 3 equals 8?

3==8
3==5
3 != 8
4!=4
2!=4
3 <= 8
3>4

TRUE | FALSE
FALSE | FALSE

TRUE & FALSE

!FALSE

!TRUE

!FALSE & FALSE | TRUE
!FALSE & !TRUE | TRUE

2>5|1==3
11>7|4==3

log (10) #ln, natural log, base e=2.72

log10 (10)
log10 (100)
log10 (1000)

#Question_1: Compute the log base 5 of 10 and the log of 10.

log (10, base = 5)
log10(10)

#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

Batting_Average=round(BA,digits = 3)
Batting_Average

#Question_2:What is the batting average of a player that bats 42 hits in 212 at bats?

BA_1=(42)/212
Batting_Average1=round(BA_1,digits = 3)
Batting_Average1

#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

On_Base_Percentage=round(OBP,digits = 3)
On_Base_Percentage

#Question_3:Compute the OBP for a player with the following general stats: #AB=565,H=156,BB=65,HBP=3,SF=7

OBP=(156+65+3)/(565+65+3+7)
On_Base_Percentage=round(OBP,digits = 3)
On_Base_Percentage

Total_Bases <- 136+214
Total_Bases

ls()

rm(Total_Bases)

ls()

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

Wins_Season<-c(94,88,96,87,79)
Wins_Season

strikes_by_innings <- c(5, 6, 9, 7, 14)
strikes_by_innings

rep(2, 5)

1:6
seq(3,10,3)

strikes_by_innings
Wins_Season
pitches_by_innings

strikes_by_innings+pitches_by_innings
strikes_by_innings==pitches_by_innings

length(pitches_by_innings)
min(pitches_by_innings)
max(pitches_by_innings)
mean(pitches_by_innings)

pitches_by_innings[3]
pitches_by_innings[1]
pitches_by_innings[5]

pitches_by_innings[length(pitches_by_innings)]

pitches_by_innings[c(2,3,4)]

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

soccer_positions <- c("goalkeeper", "defender", "Midfield", "forwards")
soccer_positions

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(1:9,size = 2)

x <- c("Yes","No","No","No","Yes","Yes","Yes","Yes","Yes","Yes") 
x
table(x)

sals <- c(12, .4, 5, 2, 50, 8, 3, 1, 4, 0.25)
mean(sals) 

var(sals)
sd(sals)
median(sals)

# Tukey's five number summary, usefull for boxplots
# five numbers: min, lower hinge, median, upper hinge, max
fivenum(sals)

summary(sals)

# Function to find the mode, i.e. most frequent value
getMode <- function(x) {
     ux <- unique(x)
     ux[which.max(tabulate(match(x, ux)))]
 }

getMode(pitches_by_innings)

getMode(Wins_Season)
Wins_Season

#Question_8: Summarize the following survey with the `table()` command:
#What is your favorite day of the week to watch baseball? A total of 10 fans submitted this survey.
#Saturday, Saturday, Sunday, Monday, Saturday,Tuesday, Sunday, Friday, Friday, Monday
game_day<-c("Saturday", "Saturday", "Sunday", "Monday", "Saturday","Tuesday", "Sunday", "Friday", "Friday", "Monday")

table(game_day)

getMode(game_day)