1 Diameter

In this exercise, we utilized the log() function to get the logarithm values of the diameter given from 100 samples.

1.1 Results

The values before the operation were roughly 10 and after, they were around 2.

dat2 <- read.csv("https://raw.githubusercontent.com/tmatis12/datafiles/main/diameter.csv")
head(dat2)
##   Diameter
## 1   10.261
## 2   10.031
## 3   10.203
## 4   10.245
## 5   10.389
## 6    9.803
dat2 <- log(dat2$Diameter)
head(dat2)
## [1] 2.328350 2.305680 2.322682 2.326790 2.340748 2.282688
diameter_log.csv <-write.csv(dat2)
## "","x"
## "1",2.32835030088007
## "2",2.30568029790135
## "3",2.32268179469317
## "4",2.32678978169086
## "5",2.34074755408839
## "6",2.28268846127959
## "7",2.36264484942171
## "8",2.31144572142624
## "9",2.31243640904442
## "10",2.33621327397403
## "11",2.34007353740504
## "12",2.36668601840057
## "13",2.30178477282328
## "14",2.32395511873024
## "15",2.35261258659369
## "16",2.32317172660243
## "17",2.3070749982669
## "18",2.35726265428474
## "19",2.33959181862314
## "20",2.33804875726961
## "21",2.29515757716525
## "22",2.29867746816303
## "23",2.27191967868316
## "24",2.3060789822483
## "25",2.34554879242616
## "26",2.31104917140618
## "27",2.35099423220173
## "28",2.29917929985921
## "29",2.3068758744112
## "30",2.29364525142457
## "31",2.341901955371
## "32",2.31530386540182
## "33",2.32796039932527
## "34",2.32951909423413
## "35",2.31015635849036
## "36",2.29384702705076
## "37",2.30747312706682
## "38",2.32179931191785
## "39",2.32434658477556
## "40",2.31184211425672
## "41",2.31983544640057
## "42",2.32503128182388
## "43",2.33872413960992
## "44",2.29435128806694
## "45",2.29273675693923
## "46",2.28136145654242
## "47",2.28554065838479
## "48",2.29727099817028
## "49",2.33524587523359
## "50",2.32405299960929
## "51",2.3425747412102
## "52",2.33194970162395
## "53",2.30028244393137
## "54",2.31243640904442
## "55",2.32552006427654
## "56",2.30836833774977
## "57",2.34526136727448
## "58",2.33833826269986
## "59",2.32864262731334
## "60",2.29737152594116
## "61",2.31045405137274
## "62",2.30637789123274
## "63",2.35223203288346
## "64",2.33233805114339
## "65",2.33534265723222
## "66",2.30627826483166
## "67",2.30438347493543
## "68",2.34813190795002
## "69",2.31095000932567
## "70",2.33029753156058
## "71",2.34860953130533
## "72",2.29696935420841
## "73",2.31816312295736
## "74",2.29314063416605
## "75",2.26519470377549
## "76",2.32111239760793
## "77",2.3254223268968
## "78",2.3112474660727
## "79",2.35242232784122
## "80",2.31589610705372
## "81",2.27572763882416
## "82",2.33146405254442
## "83",2.30737360972584
## "84",2.31609344301884
## "85",2.28716684026567
## "86",2.35403837458296
## "87",2.29958058397375
## "88",2.3349554730245
## "89",2.27439135862326
## "90",2.31233738443672
## "91",2.29566117792122
## "92",2.32209355938209
## "93",2.33010297903079
## "94",2.33968818094555
## "95",2.34315105474071
## "96",2.33534265723222
## "97",2.34045874542213
## "98",2.34860953130533
## "99",2.29666761923001
## "100",2.3263992710933
plot(dat2)