library(rmarkdown); library(knitr); library(moments);
library(scatterplot3d); library(corrplot); library(pso)
library(psych); library(GPArotation); library(lavaan)isleRoyale <- matrix(c(20, 538, NA, NA, 20,
22, 564, NA, NA, 14.3,
22, 572, NA, NA, 19.5,
23, 579, NA, NA, 16.5,
20, 596, NA, NA, 21.2,
26, 620, NA, NA, 15.9,
28, 634, NA, NA, 13.2,
26, 661, NA, NA, 18,
22, 766, NA, NA, 21,
22, 848, NA, NA, 20,
17, 1041, NA, NA, 16.5,
18, 1045, NA, NA, 16.1,
20, 1183, 0.615, 0.062, 11.4,
23, 1243, 0.819, 0.091, 10.7,
24, 1215, 0.760, 0.090, 15.1,
31, 1203, 0.599, 0.093, 14.7,
41, 1139, 0.645, 0.139, 12.3,
44, 1070, 0.563, 0.139, 10.3,
34, 949, 0.298, 0.064, 6.1,
40, 845, 0.507, 0.144, 10.2,
43, 857, 0.387, 0.117, 13,
50, 788, 0.330, 0.126, 12,
30, 767, 0.217, 0.051, 23.7,
14, 780, 0.869, 0.094, 20.7,
23, 830, 0.394, 0.065, 16.4,
24, 927, 0.440, 0.068, 14.5,
22, 976, 0.457, 0.062, 13.1,
20, 1014, 0.670, 0.079, 16,
16, 1046, 0.549, 0.050, 16,
12, 1116, 0.864, 0.056, 15.2,
12, 1260, 0.810, 0.046, 13.4,
15, 1315, 0.857, 0.059, 14.8,
12, 1496, 1.029, 0.050, 13.9,
12, 1697, 1.428, 0.061, 10.9,
13, 1784, 0.877, 0.038, 14,
17, 2017, 0.792, 0.040, 12,
16, 2117, 1.391, 0.063, 7,
22, 2398, 1.274, 0.070, 3),
byrow = T, nrow = 38, ncol = 5,
dimnames = list(c(1959:1996),
c("Wolves","Moose","Kill Rate","Predation Rate","Moose Recruitment Rate")))
isleRoyale## Wolves Moose Kill Rate Predation Rate Moose Recruitment Rate
## 1959 20 538 NA NA 20.0
## 1960 22 564 NA NA 14.3
## 1961 22 572 NA NA 19.5
## 1962 23 579 NA NA 16.5
## 1963 20 596 NA NA 21.2
## 1964 26 620 NA NA 15.9
## 1965 28 634 NA NA 13.2
## 1966 26 661 NA NA 18.0
## 1967 22 766 NA NA 21.0
## 1968 22 848 NA NA 20.0
## 1969 17 1041 NA NA 16.5
## 1970 18 1045 NA NA 16.1
## 1971 20 1183 0.615 0.062 11.4
## 1972 23 1243 0.819 0.091 10.7
## 1973 24 1215 0.760 0.090 15.1
## 1974 31 1203 0.599 0.093 14.7
## 1975 41 1139 0.645 0.139 12.3
## 1976 44 1070 0.563 0.139 10.3
## 1977 34 949 0.298 0.064 6.1
## 1978 40 845 0.507 0.144 10.2
## 1979 43 857 0.387 0.117 13.0
## 1980 50 788 0.330 0.126 12.0
## 1981 30 767 0.217 0.051 23.7
## 1982 14 780 0.869 0.094 20.7
## 1983 23 830 0.394 0.065 16.4
## 1984 24 927 0.440 0.068 14.5
## 1985 22 976 0.457 0.062 13.1
## 1986 20 1014 0.670 0.079 16.0
## 1987 16 1046 0.549 0.050 16.0
## 1988 12 1116 0.864 0.056 15.2
## 1989 12 1260 0.810 0.046 13.4
## 1990 15 1315 0.857 0.059 14.8
## 1991 12 1496 1.029 0.050 13.9
## 1992 12 1697 1.428 0.061 10.9
## 1993 13 1784 0.877 0.038 14.0
## 1994 17 2017 0.792 0.040 12.0
## 1995 16 2117 1.391 0.063 7.0
## 1996 22 2398 1.274 0.070 3.0# Insert code or written answer here
nrow(isleRoyale)## [1] 38ncol(isleRoyale)## [1] 5# Insert code or written answer here
head(isleRoyale, n = 3)## Wolves Moose Kill Rate Predation Rate Moose Recruitment Rate
## 1959 20 538 NA NA 20.0
## 1960 22 564 NA NA 14.3
## 1961 22 572 NA NA 19.5# Insert code or written answer here
isleRoyale[7, "Wolves"]## [1] 28# Insert code or written answer here
isleRoyale[13, "Moose"]## [1] 1183# Insert code or written answer here
isleRoyale["1981", c("Wolves", "Moose")]## Wolves Moose
## 30 767# Insert code or written answer here
poverty <- matrix(
c(
0.3,0.0,0.4,1.5,
7.4,4.9,16.3,13.2,
1.7,0.2,34.2,16.0,
0.1,0.3,0.6,4.0,
2.4,1.3,8.2,5.1,
4.3,1.4,3.6,3.9,
2.1,0.3,9.0,6.3,
6.2,4.1,12.1,5.4,
0.5,0.1,1.0,2.0
),
ncol = 4,
byrow = TRUE
)
rownames(poverty) <- c("Argentina","Bolivia","Brazil","Chile","Colombia","Ecuador","Paraguay","Peru","Uruguay")
colnames(poverty) <- c("Water","Electricity","Sanitation","Education")# Insert code or written answer here
dim(poverty)## [1] 9 4# Insert code or written answer here
poverty[, c("Electricity","Education")]## Electricity Education
## Argentina 0.0 1.5
## Bolivia 4.9 13.2
## Brazil 0.2 16.0
## Chile 0.3 4.0
## Colombia 1.3 5.1
## Ecuador 1.4 3.9
## Paraguay 0.3 6.3
## Peru 4.1 5.4
## Uruguay 0.1 2.0# Insert code or written answer here
poverty["Chile","Sanitation"] <- 2.4# Insert code or written answer here
which(poverty > 10, arr.ind = TRUE)## row col
## Bolivia 2 3
## Brazil 3 3
## Peru 8 3
## Bolivia 2 4
## Brazil 3 4# Insert code or written answer here
poverty[poverty > 10] <- 10
poverty## Water Electricity Sanitation Education
## Argentina 0.3 0.0 0.4 1.5
## Bolivia 7.4 4.9 10.0 10.0
## Brazil 1.7 0.2 10.0 10.0
## Chile 0.1 0.3 2.4 4.0
## Colombia 2.4 1.3 8.2 5.1
## Ecuador 4.3 1.4 3.6 3.9
## Paraguay 2.1 0.3 9.0 6.3
## Peru 6.2 4.1 10.0 5.4
## Uruguay 0.5 0.1 1.0 2.0# Insert code or written answer here
A <- matrix(c(4,3,8), nrow = 1) # row of 3 numbers
B <- matrix(9, nrow = 1, ncol = 1) # single number
C <- matrix(c(7,6,5,1), nrow = 2, byrow = TRUE) # 2x2 block
D <- matrix(2, nrow = 1, ncol = 1) # single number# Insert code or written answer here
middle_row <- cbind(B, C[2, , drop = FALSE]) # [9 5 1]
bottom_row <- cbind(D, C[1, , drop = FALSE]) # [2 7 6]
magic <- rbind(A, middle_row, bottom_row)
magic## [,1] [,2] [,3]
## [1,] 4 3 8
## [2,] 9 5 1
## [3,] 2 7 6# Insert code or written answer here
rowSums(magic)## [1] 15 15 15colSums(magic)## [1] 15 15 15# Insert code or written answer here
sum(diag(magic))## [1] 15# Insert code or written answer here# Insert code or written answer here# Insert code or written answer here
pres <- matrix(
c(
68,15.4,
74,22.6,
59,23.2,
45,-2.1,
37,-0.7,
58,18.2,
35,-5.5,
54,8.5,
48,2.4,
52,3.9,
45,-4.4
),
ncol = 2,
byrow = TRUE
)
rownames(pres) <- c("Eisenhower1956","Johnson1964","Nixon1972","Ford1976",
"Carter1980","Reagan1984","BushSr1992","Clinton1996",
"BushJr2004","Obama2012","Trump2020")
colnames(pres) <- c("Approval","Margin")# Insert code or written answer here
which(pres[,"Approval"] < 50)## Ford1976 Carter1980 BushSr1992 BushJr2004 Trump2020
## 4 5 7 9 11# Insert code or written answer here
which(pres[,"Margin"] < 0)## Ford1976 Carter1980 BushSr1992 Trump2020
## 4 5 7 11The difference is that Bush Jr. (2004) shows up only in the first list. The heading states that since 1950, all incumbents with an approval rating of 50% or higher leading up to an election have won, whereas almost all presidents with approval ratings lower than 50% have lost. However, Bush Jr has an approval rate below 50 (in the first list), but he still won (margin is 2.4)
# Insert code or written answer here# Insert code or written answer here# Insert code or written answer here