Example I have the database as follows:
MES RESP
1 4.67
1 5.11
2 5.22
2 4.99
3 4.60
3 5.39
4 4.98
4 5.29
5 5.82
5 5.01
6 5.90
6 4.22
7 4.40
7 4.69
How do I calculate the Variance, Mean, Standard Deviation between months 2 to 4 and 6 to 7 together? ie the Variance, Mean, Standard Deviation of the following values without having to delete anything from the database
MES RESP
2 5.22
2 4.99
3 4.60
3 5.39
4 4.98
4 5.29
6 5.90
6 4.22
7 4.40
7 4.69
What you ask can be done with functions of the *apply family, after defining a function to calculate the statistics of interest.
estatisticas <- function(x, na.rm = TRUE){
m <- mean(x, na.rm = na.rm)
v <- var(x, na.rm = na.rm)
s <- sd(x, na.rm = na.rm)
c(Media = m, Var = v, DesvPadrao = s)
}
Since only baselines with month MES from 2 to 4 and 6 or 7 are required, a subbase is created with these lines.
dados2 <- subset(dados, MES %in% c(2:4, 6:7))
First I'll calculate the statistics for each value of MES .
res <- tapply(dados2$RESP, dados2$MES, FUN = estatisticas)
res <- do.call(rbind, res)
res
# Media Var DesvPadrao
#2 5.105 0.02645 0.1626346
#3 4.995 0.31205 0.5586144
#4 5.135 0.04805 0.2192031
#6 5.060 1.41120 1.1879394
#7 4.545 0.04205 0.2050610
Now, calculate the same statistics by groups of MES , one of 2 to 4 and the other 6 or 7.
grupo <- dados2$MES %in% 6:7
res2 <- tapply(dados2$RESP, grupo, FUN = estatisticas)
res2 <- do.call(rbind, res2)
row.names(res2) <- c(paste(2:4, collapse = "."), paste(6:7, collapse = "."))
res2
# Media Var DesvPadrao
#2.3.4 5.078333 0.08165667 0.2857563
#6.7 4.802500 0.57282500 0.7568520