“PRIMERA”

A=(24/-8+7)/(9-6*2)
A
## [1] -1.333333
B=2^3*-7+4-(1/3+1/2)
B
## [1] -52.83333
C=(sqrt(16)+5*4-3^-2)/(3*(4-8)+1)
C
## [1] -2.171717
D=(1/2)*((5/4-2^-1)*13/4-(sqrt(7))+8/(2-1/5)-3^2)
D
## [1] -2.381903
E=2*sin(pi/3)+5*cos(pi/4)-tan(pi/6)/4
E
## [1] 5.123247
F=4*log(5, 2)-3*log(7, 3)+(1/3)*log(8)^3
F
## [1] 6.971203
ls.str()
## A :  num -1.33
## B :  num -52.8
## C :  num -2.17
## D :  num -2.38
## E :  num 5.12
## F :  num 6.97

“SEGUNDA”

round(A, 1)
## [1] -1.3
round(B, 1)
## [1] -52.8
round(C, 1)
## [1] -2.2
round(D, 1)
## [1] -2.4
round(E, 1)
## [1] 5.1
round(F, 1)
## [1] 7
rm()

“tercera”

x=c(1,3,5,7,9)
x
## [1] 1 3 5 7 9
y=c(2,4,6,7,11,12)
y
## [1]  2  4  6  7 11 12
x+1
## [1]  2  4  6  8 10
y*2
## [1]  4  8 12 14 22 24
length(x)
## [1] 5
length(y)
## [1] 6
 x+y
## Warning in x + y: longitud de objeto mayor no es múltiplo de la longitud de uno
## menor
## [1]  3  7 11 14 20 13
sum(x>5)
## [1] 2
sum(x[x>5])
## [1] 16
sum(x>5|x<3)
## [1] 3
y[2]
## [1] 4
y[-2]
## [1]  2  6  7 11 12
y[x]
## [1]  2  6 11 NA NA
y[y>=8]
## [1] 11 12

“cuarta”

millas = c(65241, 65665, 65998, 66014, 66547, 66857, 67025, 67447, 66958, 67002)
 millas
##  [1] 65241 65665 65998 66014 66547 66857 67025 67447 66958 67002
 kms = 1.609*(millas)
 kms
##  [1] 104972.8 105655.0 106190.8 106216.5 107074.1 107572.9 107843.2 108522.2
##  [9] 107735.4 107806.2
 diff(millas)
## [1]  424  333   16  533  310  168  422 -489   44
diff(kms)
## [1]  682.216  535.797   25.744  857.597  498.790  270.312  678.998 -786.801
## [9]   70.796
mean (millas)
## [1] 66475.4
mean (kms)
## [1] 106958.9

“quinta”

p=c(47, 32, 40, 36, 49, 31, 49, 30, 49, 35, 48, 32)
p
##  [1] 47 32 40 36 49 31 49 30 49 35 48 32
 pt=sum(p)
 pt
## [1] 478
pp=pt/12
pp
## [1] 39.83333
pmm=c(min(p), max(p))
pmm
## [1] 30 49
pm=ts(p, frequency=12, start=c(2020,1), end=c(2020,12))
pm
##      Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
## 2020  47  32  40  36  49  31  49  30  49  35  48  32
p40=sum(p>40)
p40
## [1] 5
pt=(sum(p[p>40])*100)/pt
pt
## [1] 50.62762

“sexta”

x=c(61, 88, 73, 49, 41, 72, 99, 07, 12, 13, 87, 91, 05, 17, 97)
 plot(x, ylab="Porcentaje de datos", xlab="No. datos", col = "orange")

 summary(x)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    5.00   15.00   61.00   54.13   87.50   99.00
  fivenum(x)
## [1]  5.0 15.0 61.0 87.5 99.0

“septima”

 rm()
x=rnorm(100)
 hist(x, ylab="Numero", xlab="Dato", main = "rnorm 100 numeros", col = "orange", border = "blue",)

 summary(x)
##     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
## -2.37258 -0.60332  0.15435  0.08883  0.64948  2.08669

“ocatava”

 rm(x)
 x=rbinom(30, 5, 0.9)
 x
##  [1] 5 2 5 4 3 5 4 4 4 5 5 5 5 5 4 5 5 4 4 4 4 3 4 4 5 4 5 4 5 5
 barplot(x, names.arg=c(1:30), ylab="Numero", xlab="Dato",main = "rbinom 30 numeros", col="white", border="black")

summary(x)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   2.000   4.000   4.000   4.333   5.000   5.000

“novena”

f=c(0, 1, 0, NA, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 3, 0, 0, 0, 0, 0, 2, 0, 1)
 boxplot(f,ylab="No. fallos", xlab="intentos")

 barplot(f, names.arg=c(1:23), ylab="No. fallos", xlab="Intentos",main = "Satelite en orbita", col="orange", border="blue")

mean(f,na.rm=TRUE)
## [1] 0.4545455
tabulado=tabulate(f)
 tabulado
## [1] 5 1 1

“diez”

P1=c(3,3,3,4,3,4,3,4,4,3)
P2=c(5,5,2,2,5,2,2,5,5,2)
P3=c(1,3,1,3,3,3,1,3,1,1)
P1
##  [1] 3 3 3 4 3 4 3 4 4 3
P2
##  [1] 5 5 2 2 5 2 2 5 5 2
P3
##  [1] 1 3 1 3 3 3 1 3 1 1
table(P1)
## P1
## 3 4 
## 6 4
table(P2)
## P2
## 2 5 
## 5 5
table(P3)
## P3
## 1 3 
## 5 5
tb1=table(P1,P2)
tb1
##    P2
## P1  2 5
##   3 3 3
##   4 2 2
tb2=table(P1,P3)
tb2
##    P3
## P1  1 3
##   3 4 2
##   4 1 3
tb3=table(P2,P3)
tb3
##    P3
## P2  1 3
##   2 3 2
##   5 2 3
tb4= table(P1,P2,P3)
tb4
## , , P3 = 1
## 
##    P2
## P1  2 5
##   3 3 1
##   4 0 1
## 
## , , P3 = 3
## 
##    P2
## P1  2 5
##   3 0 2
##   4 2 1
barplot(tb3)

matriz=matrix(c(P1,P2,P3),nrow=3,ncol=10,byrow=TRUE)
matriz
##      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## [1,]    3    3    3    4    3    4    3    4    4     3
## [2,]    5    5    2    2    5    2    2    5    5     2
## [3,]    1    3    1    3    3    3    1    3    1     1
barplot(matriz)

“once”

GC=c(14.2, 8.0, 9.2, 12.1, 8.7, 11.6, 11.0, 12.5, 10.0, 9.0, 8.5, 13.1, 12.9, 8.4, 11.2, 9.8, 12.4, 11.0, 13.0, 8.6)
GC
##  [1] 14.2  8.0  9.2 12.1  8.7 11.6 11.0 12.5 10.0  9.0  8.5 13.1 12.9  8.4 11.2
## [16]  9.8 12.4 11.0 13.0  8.6
NP=c(11, 10, 6, 9, 10, 12, 14, 10, 8, 9, 11, 12, 11, 11, 15, 13, 12, 12, 8, 13)
NP
##  [1] 11 10  6  9 10 12 14 10  8  9 11 12 11 11 15 13 12 12  8 13
library(modeest)
mfv(GC)
## [1] 11
mfv(NP)
## [1] 11 12
median(GC)
## [1] 11
median(NP)
## [1] 11
mean(GC)
## [1] 10.76
mean(NP)
## [1] 10.85
sd(GC)
## [1] 1.914873
sd(NP)
## [1] 2.183069
var(GC)
## [1] 3.666737
var(NP)
## [1] 4.765789
quantile(GC)
##     0%    25%    50%    75%   100% 
##  8.000  8.925 11.000 12.425 14.200
quantile(NP)
##    0%   25%   50%   75%  100% 
##  6.00  9.75 11.00 12.00 15.00
hist(GC)

hist(NP)

“doce”

PHP=c(14.0, 24.7, 16.4, 26.0, 25.7, 24.6)
PHP
## [1] 14.0 24.7 16.4 26.0 25.7 24.6
TMI=c(8.8, 10.2, 8.0, 9.1, 8.2, 9.4)
TMI
## [1]  8.8 10.2  8.0  9.1  8.2  9.4
library(modeest)
 mfv(PHP)
## [1] 14.0 16.4 24.6 24.7 25.7 26.0
mfv(TMI)
## [1]  8.0  8.2  8.8  9.1  9.4 10.2
median(PHP)
## [1] 24.65
median(TMI)
## [1] 8.95
sd(PHP)
## [1] 5.273329
sd(TMI)
## [1] 0.8093207
hist(PHP)

hist(TMI)

“trece”

 ca=c(7,12)
 s=c(14,10)
 o=c(5,10)
 t=cbind(ca,s,o)
colnames(t)=c("Casado", "Soltero", "Otro")
rownames(t)=c("Masculino", "Femenino")
 t
##           Casado Soltero Otro
## Masculino      7      14    5
## Femenino      12      10   10
barplot(ca, main = "casad@s", names.arg=c("Hombre", "mujer"), col=c("blue","white"), border="black")

 labels=c("hombre" , "mujer")
 pie(s, main="solter@s", labels, col=c("blue","white"))