In-Class Activity #5

Question #1

#Walks currently

Juan_walks <- c(79, 108,41,145,135)
Juan_walks

## [1]  79 108  41 145 135

#AVG walks wanted per season

walks_wanted <- 100

#Number of Seasons

n_seasons <- 6

# Needed Home-runs on season 5
x_6 <- n_seasons*walks_wanted - sum(Juan_walks)

# Minimum number of walks needed by Juan

x_6

## [1] 92

#Juan's performance

Juan_woks <- c(79, 108,41,145,135,92) 
mean(Juan_woks)

## [1] 100

#Standard Deviation

sd(Juan_woks)

## [1] 38.20995

#Max # of walks

max(Juan_woks)

## [1] 145

#Min # of walks

min(Juan_woks)

## [1] 41

summary(Juan_woks)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   41.00   82.25  100.00  100.00  128.25  145.00

Question #2

n_1 <- 7
n_2 <- 9
y_1 <- 102000
y_2 <- 91000

#Mean salary overall

salary_avg <- (n_1 * y_1 + n_2 * y_2)/(n_1+n_2)
salary_avg

## [1] 95812.5

Question #3

doubles_hit <- read.table("doubles_hit.csv", header = TRUE, sep = ",")
dub_hits <- doubles_hit$doubles_hit

# Mean

dub_mean <- mean(dub_hits)
dub_mean

## [1] 23.55

# Median

dub_med <- median(dub_hits)
dub_med

## [1] 23.5

# Length

dub_n <- length(dub_hits)
dub_n

## [1] 100

# Standard deviation

dub_sd <- sd(dub_hits)
dub_sd

## [1] 13.37371

# Within 1 standard deviation

dub_1sd <- sum((dub_hits - dub_mean)/dub_sd < 1)/dub_n
dub_1sd

## [1] 0.79

# Difference from empirical

dub_1sd - 0.68

## [1] 0.11

# Within 2 standard deviation

dub_2sd <- sum((dub_hits - dub_mean)/dub_sd < 2)/dub_n
dub_2sd

## [1] 1

# Difference from empirical

dub_2sd - 0.95

## [1] 0.05

# Within 3 standard deviation

dub_3sd <- sum((dub_hits - dub_mean)/dub_sd < 3)/dub_n
dub_3sd

## [1] 1

# Difference from empirical

dub_3sd - 0.9973

## [1] 0.0027

# Create a Histogram

hist(dub_hits,xlab = "Total of Doubles Hit",col ="green",border = "red",xlim = c(0,50), ylim = c(0,25), breaks = 5)