8.1 Capítulo 1

Solução. 1.6

library(coronavirus)
(s <- sum(coronavirus$cases))    # a

## [1] 814351012

(s2 <- sum(coronavirus$cases^2)) # b

## [1] 1.234264e+14

by(coronavirus$cases, coronavirus$type, sum) # c

## coronavirus$type: confirmed
## [1] 676570149
## ------------------------------------------------------------------------------------------------------ 
## coronavirus$type: death
## [1] 6881802
## ------------------------------------------------------------------------------------------------------ 
## coronavirus$type: recovery
## [1] 130899061

(n <- nrow(coronavirus))

## [1] 973836

d \(\sum_{i=1}^{973836} x_{i} = 8.1435101\times 10^{8}\)

\(\sum_{i=1}^{973836} x_{i}^2 = 1.2342636\times 10^{14}\)

library(lubridate)
today()-min(coronavirus$date) # 2021-08-05

## Time difference of 1570 days