Activity 4

#Addition
2+3

[1] 5

#Subtraction
2-5

[1] -3

#Exponents
5^3

[1] 125

log(2.72,base = 2.72)

[1] 1

log10(10)

[1] 1

log10(10)

[1] 1

log10(100)

[1] 2

log(10,base = 5)

[1] 1.430677

#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?
BA=(42)/(212)
Batting_Average=round(BA,digits = 3)
Batting_Average

[1] 0.198

#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

#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

3 <= 8# Is 3 less than or equal to 8?

[1] TRUE

3>=5

[1] FALSE

3==5

[1] FALSE

!FALSE

[1] TRUE

!TRUE

[1] FALSE

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

[1] TRUE

2>3|2==3

[1] FALSE

2>1 & 3>=3

[1] TRUE

2>1 & 3>=4

[1] FALSE

Total_Bases <- 6 + 5
Total_Bases*3

[1] 33

ls()

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

rm(Total_Bases)

ls()

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

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_9innings<-c(2,5,7,11,13)
hits_per_9innings<-c(11,13,16,18,19)
runs_per_9innings

[1]  2  5  7 11 13

hits_per_9innings

[1] 11 13 16 18 19

rep(3,4)

[1] 3 3 3 3

2:4

[1] 2 3 4

#Sequence
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

runs_per_9innings==hits_per_9innings

[1] FALSE FALSE FALSE FALSE FALSE

# If you want to get the second element:
pitches_by_innings[2]

[1] 15

hits_per_9innings[1]

[1] 11

hits_per_9innings[length(hits_per_9innings)]

[1] 19

pitches_by_innings[c(2, 3, 4)]

[1] 15 10 20

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

[1] "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]  7  8 10  3  6

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

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

x
 No Yes 
  2   3 

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

[1] 8.565

var(sals)

[1] 225.5145

sd(sals)

[1] 15.01714

median(sals)

[1] 3.5

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

[1]  0.25  1.00  3.50  8.00 50.00

# summary statistics
summary(sals)

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  0.250   1.250   3.500   8.565   7.250  50.000 

# 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)

[1] 10

getMode(hits_per_9innings)

[1] 11

getMode(strikes_by_innings)

[1] 9

#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)

game_day
  Friday   Monday Saturday   Sunday  Tuesday 
       2        2        3        2        1 

#Question_9: What is the most frequent answer recorded in the survey? Use the getMode function to compute results. 
getMode(game_day)

[1] "Saturday"