Exercício 12

Questão 1

MRT_1F <-c(517.1468515630205, 85.13094142168089, 30.333207896694553, 12.694776264558937, 3.3041601673945418, 1.1823111717498882, 1.1892293502386786)
clock <- c(0.1, 0.5, 1, 1.5, 2, 2.5, 3)
MRT_3F <-c(156.68929936163462, 11.540837783562276, 0.4512835621696538, 0.4509797929766453, 0.4502068233039181, 0.4496185276300172, 0.4543157082191288)
MRT_5F <-c(83.90319666471157, 0.3068151086494968, 0.30522314133037304, 0.3072588968084928, 0.30655265997285697, 0.3055812715727718, 0.3053297166713006)

MRT_10F <-c(29.55430642951759, 0.19832832665772515, 0.1971923924717474, 0.19796648905716516, 0.19615594370806338, 0.2034569237883263, 0.19617420889447737)

MRT_15F <-c(11.317736530583566, 0.167364215666193, 0.16172168266811013, 0.16701085329580515, 0.1598052657153692, 0.1645934043532696, 0.16216563797118075)

MRT_sem_F <-c(11.93430909937736, 0.6095414637034009, 0.6060645101029295, 0.612167181646899, 0.6146761002685637, 0.6096747087200697, 0.6125810476877268)



plot(clock, MRT_1F, type="l", pch=3, cex=150, xlab="Time between Things requests (seconds)", ylab="Response Time (sec.)", xlim=c(0.1,3))
lines(MRT_3F, type="l", col = "yellow", pch=11)
lines(MRT_5F, type="l", col = "red", pch=1)
lines(MRT_10F, type="l", col = "blue", pch=2)
lines(MRT_15F, type="l", col = "purple", pch=5)
lines(MRT_sem_F, type="l", col = "green", pch=4)

Values <- matrix(c(MRT_sem_F, MRT_1F), nrow = 2, ncol=8, byrow=TRUE)

base <- c("w/o Fog","1 Fog")
colors <- c("grey", "black")

barplot(Values, log="y", beside=T,decreasing=T, xlab="Time between Things requests (seconds)", ylab="Response Time (s)")

legend("center", pch=c(10,10,10), col = colors , legend=base)

Questão 2

quality <- c("good","veryood", "excellent")
pricing <- c("$10-19", "$20-29", "$30-39", "$40-49")
colors <- c("red", "green", "blue")
rating <- matrix(c(53.8,33.9,2.6,0.0,43.6,54.2,60.5,21.4,2.6,11.9,36.8,78.6), nrow=3, ncol=4, byrow=T)

barplot(rating, main ="Qualidade de refeição", names.arg = pricing, xlab ="Preço", ylab = "Avaliação", col = colors)

Questão 3

tempcelsius <- (airquality$Temp-32)/(1.8)
airquality$Temp_Celsius <- tempcelsius

Temp_Celsius_Maio <- subset (x = airquality,
        subset = Month == 5 &
        Temp_Celsius > 0)
Temp_Celsius_Maio_2 <- Temp_Celsius_Maio$Temp_Celsius

hist(Temp_Celsius_Maio_2, col ="red", density = 12, main ="Histograma de Temperaturas em Maio", xlab = "Temperatura em Celsius", breaks=15, ylab = "Frequência", freq = F)
densityTemp <- density(Temp_Celsius_Maio_2)
lines(densityTemp)

Questão 4

sales <- read.table("https://training-course-material.com/images/8/8f/Sales.txt",header=TRUE)
vendas <- sales$SALES

labels <- c("US", "UK", "France", "Poland", "Japan", "China")
pct <- round(vendas/sum(vendas)*100)
lbls <- paste (labels, pct)
lbls <- paste(lbls, "%", sep="")
pie(vendas,labels=lbls, main = "Gráfico de Vendas", col =rainbow(6))

Questão 5

m <- InsectSprays
boxplot(count ~ spray, data=InsectSprays, xlab = "Tipo de Inseticidas", ylab = "Contagem", main="Dados de Inseticidas", outline=F, col="yellow")