# Set random seed for reproducibility
set.seed(123)
# Generate 100 random numbers between 0-100
random_numbers <- runif(100, min = 0, max = 100)
random_numbers <- sort(random_numbers)
random_numbers
## [1] 0.06247733 2.46136845 4.20595335 4.55564994 4.58311667 9.35949867
## [7] 9.48406609 10.28646443 10.29246827 11.11354243 12.18992600 12.75316502
## [13] 13.06956916 13.88060634 14.28000224 14.71136473 15.24447477 17.50526503
## [19] 18.76911193 20.65313896 21.64079358 22.01188852 23.16257854 23.30340995
## [25] 24.36194727 24.60877344 26.59726404 27.43836446 28.75775201 28.91597373
## [31] 31.81810076 32.03732425 32.79207193 34.35164723 35.17979092 36.88454509
## [37] 37.44627759 37.98165377 38.39696378 40.89769218 41.37243263 41.45463358
## [43] 41.76467797 43.48927415 43.98316876 44.22000742 44.85163414 45.33341562
## [49] 45.66147353 46.59624503 46.67790416 47.53165741 47.77959711 51.15054599
## [55] 52.81054880 54.40660247 55.14350145 56.09479838 57.26334020 59.41420204
## [61] 61.27710033 62.92211316 64.05068138 65.31019250 65.57057991 65.67581280
## [67] 66.51151946 66.80555874 67.75706355 69.07052784 69.28034062 70.85304682
## [73] 71.01824014 75.33078643 75.44751586 75.84595375 78.22943013 78.81958340
## [79] 78.83051354 79.43423211 79.54674177 79.89248456 81.00643530 81.23895095
## [85] 81.46400389 85.78277153 88.30174040 88.64690608 88.95393161 89.24190444
## [91] 89.30511144 89.50453592 89.98249704 90.22990451 94.04672843 95.45036491
## [97] 95.68333453 96.30242325 98.49569800 99.42697766
# Split these random numbers into groups of 10
groups <- split(random_numbers, ceiling(seq_along(random_numbers)/10))
groups
## $`1`
## [1] 0.06247733 2.46136845 4.20595335 4.55564994 4.58311667 9.35949867
## [7] 9.48406609 10.28646443 10.29246827 11.11354243
##
## $`2`
## [1] 12.18993 12.75317 13.06957 13.88061 14.28000 14.71136 15.24447 17.50527
## [9] 18.76911 20.65314
##
## $`3`
## [1] 21.64079 22.01189 23.16258 23.30341 24.36195 24.60877 26.59726 27.43836
## [9] 28.75775 28.91597
##
## $`4`
## [1] 31.81810 32.03732 32.79207 34.35165 35.17979 36.88455 37.44628 37.98165
## [9] 38.39696 40.89769
##
## $`5`
## [1] 41.37243 41.45463 41.76468 43.48927 43.98317 44.22001 44.85163 45.33342
## [9] 45.66147 46.59625
##
## $`6`
## [1] 46.67790 47.53166 47.77960 51.15055 52.81055 54.40660 55.14350 56.09480
## [9] 57.26334 59.41420
##
## $`7`
## [1] 61.27710 62.92211 64.05068 65.31019 65.57058 65.67581 66.51152 66.80556
## [9] 67.75706 69.07053
##
## $`8`
## [1] 69.28034 70.85305 71.01824 75.33079 75.44752 75.84595 78.22943 78.81958
## [9] 78.83051 79.43423
##
## $`9`
## [1] 79.54674 79.89248 81.00644 81.23895 81.46400 85.78277 88.30174 88.64691
## [9] 88.95393 89.24190
##
## $`10`
## [1] 89.30511 89.50454 89.98250 90.22990 94.04673 95.45036 95.68333 96.30242
## [9] 98.49570 99.42698
# Randomly select one number from each group
selected_numbers <- sapply(groups, function(x) sample(x, 1))
# Display results
print(selected_numbers)
## 1 2 3 4 5 6 7 8
## 10.29247 13.88061 24.60877 38.39696 45.66147 55.14350 64.05068 78.81958
## 9 10
## 88.95393 89.98250
####################################################################################
# Group numbers by their decade intervals (1-10, 11-20, etc.)
intervals <- cut(random_numbers, breaks = seq(0, 100, by = 10),
labels = paste(seq(1, 91, by = 10), seq(10, 100, by = 10), sep = "-"))
random_numbers; intervals
## [1] 0.06247733 2.46136845 4.20595335 4.55564994 4.58311667 9.35949867
## [7] 9.48406609 10.28646443 10.29246827 11.11354243 12.18992600 12.75316502
## [13] 13.06956916 13.88060634 14.28000224 14.71136473 15.24447477 17.50526503
## [19] 18.76911193 20.65313896 21.64079358 22.01188852 23.16257854 23.30340995
## [25] 24.36194727 24.60877344 26.59726404 27.43836446 28.75775201 28.91597373
## [31] 31.81810076 32.03732425 32.79207193 34.35164723 35.17979092 36.88454509
## [37] 37.44627759 37.98165377 38.39696378 40.89769218 41.37243263 41.45463358
## [43] 41.76467797 43.48927415 43.98316876 44.22000742 44.85163414 45.33341562
## [49] 45.66147353 46.59624503 46.67790416 47.53165741 47.77959711 51.15054599
## [55] 52.81054880 54.40660247 55.14350145 56.09479838 57.26334020 59.41420204
## [61] 61.27710033 62.92211316 64.05068138 65.31019250 65.57057991 65.67581280
## [67] 66.51151946 66.80555874 67.75706355 69.07052784 69.28034062 70.85304682
## [73] 71.01824014 75.33078643 75.44751586 75.84595375 78.22943013 78.81958340
## [79] 78.83051354 79.43423211 79.54674177 79.89248456 81.00643530 81.23895095
## [85] 81.46400389 85.78277153 88.30174040 88.64690608 88.95393161 89.24190444
## [91] 89.30511144 89.50453592 89.98249704 90.22990451 94.04672843 95.45036491
## [97] 95.68333453 96.30242325 98.49569800 99.42697766
## [1] 1-10 1-10 1-10 1-10 1-10 1-10 1-10 11-20 11-20 11-20
## [11] 11-20 11-20 11-20 11-20 11-20 11-20 11-20 11-20 11-20 21-30
## [21] 21-30 21-30 21-30 21-30 21-30 21-30 21-30 21-30 21-30 21-30
## [31] 31-40 31-40 31-40 31-40 31-40 31-40 31-40 31-40 31-40 41-50
## [41] 41-50 41-50 41-50 41-50 41-50 41-50 41-50 41-50 41-50 41-50
## [51] 41-50 41-50 41-50 51-60 51-60 51-60 51-60 51-60 51-60 51-60
## [61] 61-70 61-70 61-70 61-70 61-70 61-70 61-70 61-70 61-70 61-70
## [71] 61-70 71-80 71-80 71-80 71-80 71-80 71-80 71-80 71-80 71-80
## [81] 71-80 71-80 81-90 81-90 81-90 81-90 81-90 81-90 81-90 81-90
## [91] 81-90 81-90 81-90 91-100 91-100 91-100 91-100 91-100 91-100 91-100
## Levels: 1-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100
groups <- split(random_numbers, intervals)
groups
## $`1-10`
## [1] 0.06247733 2.46136845 4.20595335 4.55564994 4.58311667 9.35949867 9.48406609
##
## $`11-20`
## [1] 10.28646 10.29247 11.11354 12.18993 12.75317 13.06957 13.88061 14.28000
## [9] 14.71136 15.24447 17.50527 18.76911
##
## $`21-30`
## [1] 20.65314 21.64079 22.01189 23.16258 23.30341 24.36195 24.60877 26.59726
## [9] 27.43836 28.75775 28.91597
##
## $`31-40`
## [1] 31.81810 32.03732 32.79207 34.35165 35.17979 36.88455 37.44628 37.98165
## [9] 38.39696
##
## $`41-50`
## [1] 40.89769 41.37243 41.45463 41.76468 43.48927 43.98317 44.22001 44.85163
## [9] 45.33342 45.66147 46.59625 46.67790 47.53166 47.77960
##
## $`51-60`
## [1] 51.15055 52.81055 54.40660 55.14350 56.09480 57.26334 59.41420
##
## $`61-70`
## [1] 61.27710 62.92211 64.05068 65.31019 65.57058 65.67581 66.51152 66.80556
## [9] 67.75706 69.07053 69.28034
##
## $`71-80`
## [1] 70.85305 71.01824 75.33079 75.44752 75.84595 78.22943 78.81958 78.83051
## [9] 79.43423 79.54674 79.89248
##
## $`81-90`
## [1] 81.00644 81.23895 81.46400 85.78277 88.30174 88.64691 88.95393 89.24190
## [9] 89.30511 89.50454 89.98250
##
## $`91-100`
## [1] 90.22990 94.04673 95.45036 95.68333 96.30242 98.49570 99.42698
# Select one random number from each decade
selected_numbers <- sapply(groups, function(x) sample(x, 1))
# Print selected numbers
print(selected_numbers)
## 1-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80
## 9.359499 13.880606 22.011889 37.446278 43.983169 52.810549 65.570580 75.845954
## 81-90 91-100
## 89.241904 95.450365