ksi = c(122.2, 124.2, 124.3, 125.6, 126.3, 126.5, 126.5, 127.2, 127.3,
127.5, 127.9, 128.6, 128.8, 129.0, 129.2, 129.4, 129.6, 130.2,
130.4, 130.8, 131.3, 131.4, 131.4, 131.5, 131.6, 131.6, 131.8,
131.8, 132.3, 132.4, 132.4, 132.5, 132.5, 132.5, 132.5, 132.6,
132.7, 132.9, 133.0, 133.1, 133.1, 133.1, 133.1, 133.2, 133.2,
133.2, 133.3, 133.3, 133.5, 133.5, 133.5, 133.8, 133.9, 134.0,
134.0, 134.0, 134.0, 134.1, 134.2, 134.3, 134.4, 134.4, 134.6,
134.7, 134.7, 134.7, 134.8, 134.8, 134.8, 134.9, 134.9, 135.2,
135.2, 135.2, 135.3, 135.3, 135.4, 135.5, 135.5, 135.6, 135.6,
135.7, 135.8, 135.8, 135.8, 135.8, 135.8, 135.9, 135.9, 135.9,
135.9, 136.0, 136.0, 136.1, 136.2, 136.2, 136.3, 136.4, 136.4,
136.6, 136.8, 136.9, 136.9, 137.0, 137.1, 137.2, 137.6, 137.6,
137.8, 137.8, 137.8, 137.9, 137.9, 138.2, 138.2, 138.3, 138.3,
138.4, 138.4, 138.4, 138.5, 138.5, 138.6, 138.7, 138.7, 139.0,
139.1, 139.5, 139.6, 139.8, 139.8, 140.0, 140.0, 140.7, 140.7,
140.9, 140.9, 141.2, 141.4, 141.5, 141.6, 142.9, 143.4, 143.5,
143.6, 143.8, 143.8, 143.9, 144.1, 144.5, 144.5, 147.7, 147.7)
mean(ksi)
## [1] 135.3869
median(ksi)
## [1] 135.4
mode_ksi = names(table(ksi))[table(ksi)==max(table(ksi))]
mode_ksi
## [1] "135.8"
var(ksi)
## [1] 21.0368
sd(ksi)
## [1] 4.586589
hist(ksi, xlab = "ksi",
main = "Tensile Ultimate Strength (ksi)",
breaks = 10)
summary(ksi)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 122.2 133.0 135.4 135.4 138.2 147.7
IQR = 138.2-133.0
133.0 - IQR*1.5
## [1] 125.2
138.2 + IQR*1.5
## [1] 146
ksi<=125.2
## [1] TRUE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [49] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [73] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [85] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [97] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [109] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [121] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [133] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [145] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
ksi>=146
## [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [49] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [73] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [85] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [97] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [109] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [121] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [133] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [145] FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE
5 total outliers were identified. 3 being less than 125.2 and 2 being greater than 146.
Finally, by identifying that the mean and median are extremely close we can say that data is symmetric if not slightly negatiely skewed.