Question 1 Answers:
#Declaring Vectors
a <- c(2, 5, 6, 7)
b <- c(1, 0, 9, 8)
c <- c(6, 5, 8, 3)
#Creating matrix (3x4)
matrix <- rbind(a, b, c)
#Setting Column Name
colnames(matrix) <- c("Mon", "Tue", "Wed", "Thu")
#Setting Row Name
rownames(matrix) <- c("Present", "Absent", "On Leave")
matrix
## Mon Tue Wed Thu
## Present 2 5 6 7
## Absent 1 0 9 8
## On Leave 6 5 8 3
rowSums <- rowSums(matrix)
rowSums
## Present Absent On Leave
## 20 18 22
colSums <- colSums(matrix)
colSums
## Mon Tue Wed Thu
## 9 10 23 18
Question 2 Answers:
#Declaring Dataset
data <- mtcars
#Assigning variables
Displacement <- data$disp
Miles_per_Gallon <- data$mpg
gear <- data$gear
data
## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
## Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
## Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
## Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
## Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
2.A
Scatterplot of mpg vs disp
Scatterplot without ggPlot2
#Scatter Plot
plot(Displacement, Miles_per_Gallon, main = 'Displacement vs Miles Per Gallon', xlab = 'Displacement', ylab = 'Miles Per Gallon', cex = 1)
abline(v = seq(100, max(Displacement), by = 100) , h = seq(min(Miles_per_Gallon), max(Miles_per_Gallon), by = 5), col = "gray", lty = "dotted")
Scatterplot With ggPlot2
# Using ggplot2 library
library(ggplot2)
plot <- ggplot(data, aes(x=Displacement, y=Miles_per_Gallon))
plot +
geom_point(color = "chartreuse", fill = "deepskyblue4", size = 3) +
geom_point(shape = 1,size = 3,colour = "deeppink") +
labs(x = "Displacement", y = "Miles per Gallon", title = 'Displacement vs Miles Per Gallon' ) +
theme(
plot.title = element_text(color="darkolivegreen", size=16, face="bold", hjust = 0.5),
axis.title.x = element_text(color="darkslategrey", size=14, face="bold"),
axis.title.y = element_text(color="#993333", size=14, face="bold"),
plot.background = element_rect(fill = "gray90"),
panel.background = element_rect(fill = "black"),
panel.grid.major = element_line(color = "blue3"),
panel.grid.minor = element_blank(),
axis.line = element_line(color = "cyan"),
axis.text = element_text(color = "black", face="bold")
)
2.B
Boxplot of mpg with gear
Boxplot Without ggPlot2
boxplot(Miles_per_Gallon ~ gear, data = mtcars, main = "Mpg with Gear Boxplot", xlab = "Gear", ylab = "Miles per Gallon")
Boxplot With ggPlot2
library(ggplot2)
plot <- ggplot(mtcars, aes(x = factor(gear), y = Miles_per_Gallon))
plot +
geom_boxplot(color = "chartreuse", fill = "deepskyblue4") +
labs(title = expression(underline("Mpg with Gear Boxplot")), x = "Gear", y = "Miles per Gallon") +
theme(
plot.title = element_text(color="darkolivegreen", size=16, hjust = 0.5),
axis.title.x = element_text(color="darkslategrey", size=14, face="bold"),
axis.title.y = element_text(color="#993333", size=14, face="bold"),
plot.background = element_rect(fill = "gray90"),
panel.background = element_rect(fill = "black"),
panel.grid.major = element_line(color = "blue3"),
panel.grid.minor = element_blank(),
axis.line = element_line(color = "cyan"),
axis.text = element_text(color = "black", face="bold")
)
2.C
Histogram of disp
#number of observations
num_observations = nrow(data)
# Calculating the total number of bins using the square root rule
num_bins <- ceiling(sqrt(num_observations))
# Calculating the bin width using Scott's rule
bin_width <- 3.5 * sd(Displacement) / num_observations
Histogram Without ggPlot2
hist(Displacement, breaks = seq(min(Displacement), max(Displacement) + bin_width, by = bin_width), main = "Histogram of Displacement", xlab = "Displacement", ylab = "Frequency")
Histogram With ggPlot2
library(ggplot2)
ggplot(mtcars, aes(x = disp)) +
geom_histogram(binwidth = bin_width, breaks = seq(min(Displacement), max(Displacement) + bin_width, by = bin_width), color = "chartreuse", fill = "deepskyblue4") +
labs(title = "Histogram of Displacement", x = "Displacement", y = "Frequency") +
theme(
plot.title = element_text(color = "darkolivegreen", size = 16, hjust = 0.5, face = "bold"),
axis.title.x = element_text(color = "darkslategrey", size = 14, face = "bold"),
axis.title.y = element_text(color = "#993333", size = 14, face = "bold"),
plot.background = element_rect(fill = "gray90"),
panel.background = element_rect(fill = "black"),
panel.grid.major = element_line(color = "blue3"),
panel.grid.minor = element_blank(),
axis.line = element_line(color = "cyan"),
axis.text = element_text(color = "black", face = "bold")
)
