Q1_2VA_CPAD

2ª VA CPAD

VADeaths

head(VADeaths)

##       Rural Male Rural Female Urban Male Urban Female
## 50-54       11.7          8.7       15.4          8.4
## 55-59       18.1         11.7       24.3         13.6
## 60-64       26.9         20.3       37.0         19.3
## 65-69       41.0         30.9       54.6         35.1
## 70-74       66.0         54.3       71.1         50.0

colors <- c("#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e")

barplot(
  height = VADeaths, 
  beside = TRUE,
  col = colors,
  main = "Mortality Rates in Virginia (1940)",
  xlab = "Demographic Groups",
  ylab = "Mortality Rate (per 1000)",
  ylim = c(0, 100),
  legend.text = rownames(VADeaths),
  args.legend = list(x = "topright", bty = "n")
)

ClassificaçãoDoença

patients <- c("moderado", "leve", "leve", "severo", "leve", 
               "moderado", "moderado", "moderado", "leve", "leve", 
               "severo", "leve", "moderado", "moderado", "leve", 
               "severo", "moderado", "moderado", "moderado", "leve")

count <- table(patients)
pct <- round(count / sum(count) * 100)
lbls <- paste(pct, "%", sep="")

colors <- c("#1b9e77", "#d95f02", "#7570b3")

pie(count, 
    labels = lbls,
    col = colors,
    main = "Disease Stages Classification"
)

legend("topright", 
       legend = names(count),
       fill = colors,
       title = "Stages",
       cex = 1.0)

Teorema

flu_data <- read.csv("flu.csv")

table(flu_data)

## age
##    0    1    2    3    4    5    6    7    8    9   10   11   12   13   14   15 
## 6409 1307  723  504  445  368  368  300  248  271  233  270  238  281  335  396 
##   16   17   18   19   20   21   22   23   24   25   26   27   28   29   30   31 
##  544  620  696  840  923  944  986 1062 1076 1117 1105 1144 1166 1100 1075 1027 
##   32   33   34   35   36   37   38   39   40   41   42   43   44   45   46   47 
##  992  997  832  877  872  785  733  757  751  689  727  738  598  622  629  617 
##   48   49   50   51   52   53   54   55   56   57   58   59   60   61   62   63 
##  697  574  591  661  656  745  794  791  792  814  799  849  848  947  909  839 
##   64   65   66   67   68   69   70   71   72   73   74   75   76   77   78   79 
##  891  994  966 1039 1135 1154 1054 1190 1229 1221 1171 1189 1112 1030 1039  922 
##   80   81   82   83   84   85   86   87   88   89   90   91   92   93   94   95 
##  753  727  677  579  501  392  354  299  224  144  133  100   56   43   30   16 
##   96   97   98   99  100 
##   11    6    6    3    1

hist(flu_data$age, 
     freq = FALSE, 
     col = "#c4c3c0", 
     main = "Death's Age", 
     xlab = "Age",
     breaks = 30)
lines(density(flu_data$age), col = "#e7298a", lwd = 2)

n_samples <- 200
sample_size <- 35
sample_mean <- numeric(n_samples)

set.seed(13)
for(i in 1:n_samples) {
  sample <- sample(flu_data$age, size = sample_size, replace = FALSE)
  sample_mean[i] <- mean(sample)
}

hist(sample_mean, 
     probability = TRUE, 
     col = "#c4c3c0", 
     main = "Sample Mean", 
     xlab = "Age Mean",
     breaks = 20)
lines(density(sample_mean), col = "#66a61e", lwd = 2)