# Perform simple arithmetic operations
1 / 4
[1] 0.25
1 - 4
[1] -3
2 * 5
[1] 10
# Square root calculation
sqrt(9)
[1] 3
# Logarithmic operations
log(10)  # Natural log
[1] 2.302585
log(2.72)  # Approximation of log base e of Euler's number
[1] 1.000632
# Calculate and assign value to variable BA
BA <- (29) / (112)
BA  # Print the value of BA
[1] 0.2589286
Batting_Average=round(BA,digits = 3)
Batting_Average
OBP=(172+84+5)/(515+172+84+5+6)
OBP
On_Base_Percentage=round(OBP,digits = 3)
On_Base_Percentage
[1] 0.334
3 == 8# Does 3 equals 8
3 != 8# Is 3 different from 8?
3 <= 8# Is 3 less than or equal to 8?
3>4
# Logical Disjunction (or)
FALSE | FALSE # False OR False
[1] FALSE
 FALSE
[1] FALSE
# 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"   
[3] "OBP"                "On_Base_Percentage"
[5] "Total_Bases"       
rm(Total_Bases)
Warning in rm(Total_Bases) : object 'Total_Bases' not found
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
# replicate function
rep(2, 5)
[1] 2 2 2 2 2
rep(1,4)
[1] 1 1 1 1
# 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, 10, by=2)
[1] 1 3 5 7 9
seq(2,13,by=3)
[1]  2  5  8 11
# 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
# 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 length of vector
length(pitches_by_innings)
[1] 5
# find minimum value in vector
min(pitches_by_innings)
[1] 10
# find average value in vector
mean(pitches_by_innings)
[1] 13.4
pitches_by_innings
[1] 12 15 10 20 10
pitches_by_innings[1]
[1] 12
pitches_by_innings[length(pitches_by_innings)]
[1] 10
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] 3 4 8 6 9
bar <- data.frame(var1 = LETTERS[1:10], var2 = 1:10)
# Check data frame
bar
n <- 5
n
[1] 5
samplerows <- sample(1:nrow(bar), size=n) 
# print sample rows
samplerows
[1] 7 6 1 3 5
# extract rows
barsample <- bar[samplerows, ]
# print sample
print(barsample)
bar[sample(1:nrow(bar), n), ]
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
# the variance
var(sals)
[1] 225.5145
# the standard deviation
sd(sals)
[1] 15.01714
# the median
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)))]
}
#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")
getMode(game_day)
[1] "Saturday"
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