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Auto-generated via `{sandpaper}` Source : a9c99b1 Branch : main Author : Christian Knudsen <[email protected]> Time : 2024-11-18 13:03:27 +0000 Message : Merge pull request KUBDatalab#191 from chrbknudsen/main metadata og et par issues
chrbknudsen · Nov 18, 2024 · e8ce106 · e8ce106
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diff --git a/clt.md b/clt.md
@@ -45,7 +45,7 @@ mean(random_numbers)
 ```
 
 ``` output
-[1] 0.5239264
+[1] 0.5098915
 ```
 The important point of the Central Limit Theorem is, that if we take a large
 number of random samples, and calculate the mean of each of these samples,
@@ -59,7 +59,7 @@ mean(runif(100))
 ```
 
 ``` output
-[1] 0.438941
+[1] 0.5483137
 ```
 And we can use the `replicate()` function to repeat that calculation several times, in this case 1000 times:
 

diff --git a/data.md b/data.md
@@ -1555,17 +1555,19 @@ NB: Filen er semikolon-separeret
 
 ::::
 
-## References
-
-
-
-
 
+### Wine
 
+A data set containing the results of a chemical analysis of three different
+cultivars (variety of grape), from the same region in Italy.
+We are provided with 13 different quantities.
 
+Usable for PCA and RDA. Note that this data set does not have column-names.
 
 
+_Dimensions:_ Rows: 178 Columns: 14 
 
+[Source](learners/data.md#wine_9)^9^
 
 @misc{misc_wine_109,
   author       = {Aeberhard,Stefan and Forina,M.},
@@ -1575,6 +1577,49 @@ NB: Filen er semikolon-separeret
   note         = {{DOI}: https://doi.org/10.24432/C5PC7J}
 }
 
+[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/wine.data)
+
+:::: spoiler
+
+## Metadata
+
+|  Variable  |  Description                      |  Unit            |
+|------------|-----------------------------------|----------------------------|
+|1      |  Cultivar                        |                            | 
+|2        | Alcohol                    |                %            | 
+|3        | Malic acid                    |         g/L                   | 
+|4        | Ash                                 |   g/L                     |         
+|5        | Alcalinity of ash       |   meq/L <br> (milliequivalents per liter)     | 
+|6        | Magnesium                |        mg/L                   |
+|7         | Total phenols                    g/L             |    |
+|8        | Flavanoids               |        g/L                  |
+|9    | Nonflavanoid phenols  |              g/L            |
+|10       | Proanthocyanins  |               g/L             |
+|11       | Color intensity  |   Absorbance                         |
+|12       | Hue  |  Absorbance-ratio             |
+|13       | OD280/OD315 of diluted wines  | Absorbance-ratio                           |
+|14       | Proline  |  mg/L                          |
+
+Absorbance is measured as the sum of absorbance-units at 420, 520 and 620 nm (blue, green and red light respectively, measuring the yellow, red, and blue colors of the wine.)
+
+Hue is measured as  absorbance at 420 nm divided by absorbance at 520 nm.
+
+OD280/OD315 is measured as absorbance at 280 nm divided by absorbance at 315 nm.
+
+::::
+
+
+
+## References
+
+
+
+
+
+
+
+
+
 
 
 
@@ -1608,6 +1653,12 @@ https://www.jstor.org/stable/2532505
 Use of antimicrobial drugs in general hospitals. I. Description for population and definition of
 methods. Journal of Infetious Diseases, 139(6), 688-697.
 
+
+< id = "wine_9">9</a>: Aeberhard, S. & Forina, M. 1991, UCI Machine Learning Repository, https://doi.org/10.24432/C5PC7J
+
+
+
+
 ## listen over datasæt. 
 Der hakkes af efterhånden som de er færdige - og så er issue 113 done.
 
@@ -1626,4 +1677,4 @@ Der hakkes af efterhånden som de er færdige - og så er issue 113 done.
 * tennis2
 * valid
 * spermatozoa
-* who
+* who
diff --git a/data/wine.data b/data/wine.data
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+3,12.25,3.88,2.2,18.5,112,1.38,.78,.29,1.14,8.21,.65,2,855
+3,13.16,3.57,2.15,21,102,1.5,.55,.43,1.3,4,.6,1.68,830
+3,13.88,5.04,2.23,20,80,.98,.34,.4,.68,4.9,.58,1.33,415
+3,12.87,4.61,2.48,21.5,86,1.7,.65,.47,.86,7.65,.54,1.86,625
+3,13.32,3.24,2.38,21.5,92,1.93,.76,.45,1.25,8.42,.55,1.62,650
+3,13.08,3.9,2.36,21.5,113,1.41,1.39,.34,1.14,9.40,.57,1.33,550
+3,13.5,3.12,2.62,24,123,1.4,1.57,.22,1.25,8.60,.59,1.3,500
+3,12.79,2.67,2.48,22,112,1.48,1.36,.24,1.26,10.8,.48,1.47,480
+3,13.11,1.9,2.75,25.5,116,2.2,1.28,.26,1.56,7.1,.61,1.33,425
+3,13.23,3.3,2.28,18.5,98,1.8,.83,.61,1.87,10.52,.56,1.51,675
+3,12.58,1.29,2.1,20,103,1.48,.58,.53,1.4,7.6,.58,1.55,640
+3,13.17,5.19,2.32,22,93,1.74,.63,.61,1.55,7.9,.6,1.48,725
+3,13.84,4.12,2.38,19.5,89,1.8,.83,.48,1.56,9.01,.57,1.64,480
+3,12.45,3.03,2.64,27,97,1.9,.58,.63,1.14,7.5,.67,1.73,880
+3,14.34,1.68,2.7,25,98,2.8,1.31,.53,2.7,13,.57,1.96,660
+3,13.48,1.67,2.64,22.5,89,2.6,1.1,.52,2.29,11.75,.57,1.78,620
+3,12.36,3.83,2.38,21,88,2.3,.92,.5,1.04,7.65,.56,1.58,520
+3,13.69,3.26,2.54,20,107,1.83,.56,.5,.8,5.88,.96,1.82,680
+3,12.85,3.27,2.58,22,106,1.65,.6,.6,.96,5.58,.87,2.11,570
+3,12.96,3.45,2.35,18.5,106,1.39,.7,.4,.94,5.28,.68,1.75,675
+3,13.78,2.76,2.3,22,90,1.35,.68,.41,1.03,9.58,.7,1.68,615
+3,13.73,4.36,2.26,22.5,88,1.28,.47,.52,1.15,6.62,.78,1.75,520
+3,13.45,3.7,2.6,23,111,1.7,.92,.43,1.46,10.68,.85,1.56,695
+3,12.82,3.37,2.3,19.5,88,1.48,.66,.4,.97,10.26,.72,1.75,685
+3,13.58,2.58,2.69,24.5,105,1.55,.84,.39,1.54,8.66,.74,1.8,750
+3,13.4,4.6,2.86,25,112,1.98,.96,.27,1.11,8.5,.67,1.92,630
+3,12.2,3.03,2.32,19,96,1.25,.49,.4,.73,5.5,.66,1.83,510
+3,12.77,2.39,2.28,19.5,86,1.39,.51,.48,.64,9.899999,.57,1.63,470
+3,14.16,2.51,2.48,20,91,1.68,.7,.44,1.24,9.7,.62,1.71,660
+3,13.71,5.65,2.45,20.5,95,1.68,.61,.52,1.06,7.7,.64,1.74,740
+3,13.4,3.91,2.48,23,102,1.8,.75,.43,1.41,7.3,.7,1.56,750
+3,13.27,4.28,2.26,20,120,1.59,.69,.43,1.35,10.2,.59,1.56,835
+3,13.17,2.59,2.37,20,120,1.65,.68,.53,1.46,9.3,.6,1.62,840
+3,14.13,4.1,2.74,24.5,96,2.05,.76,.56,1.35,9.2,.61,1.6,560
diff --git a/fig/clt-rendered-random-histogram-1.png b/fig/clt-rendered-random-histogram-1.png
diff --git a/fig/clt-rendered-repeated-means-histogram-1.png b/fig/clt-rendered-repeated-means-histogram-1.png
diff --git a/kmeans.md b/kmeans.md
@@ -144,31 +144,31 @@ clustering
 ```
 
 ``` output
-K-means clustering with 3 clusters of sizes 69, 47, 62
+K-means clustering with 3 clusters of sizes 47, 69, 62
 
 Cluster means:
    Alcohol Malicacid      Ash Alcalinityofash Magnesium Totalphenols Flavanoids
-1 12.51667  2.494203 2.288551        20.82319  92.34783     2.070725   1.758406
-2 13.80447  1.883404 2.426170        17.02340 105.51064     2.867234   3.014255
+1 13.80447  1.883404 2.426170        17.02340 105.51064     2.867234   3.014255
+2 12.51667  2.494203 2.288551        20.82319  92.34783     2.070725   1.758406
 3 12.92984  2.504032 2.408065        19.89032 103.59677     2.111129   1.584032
   Nonflavanoidphenols Proanthocyanins Colorintensity       Hue
-1           0.3901449        1.451884       4.086957 0.9411594
-2           0.2853191        1.910426       5.702553 1.0782979
+1           0.2853191        1.910426       5.702553 1.0782979
+2           0.3901449        1.451884       4.086957 0.9411594
 3           0.3883871        1.503387       5.650323 0.8839677
   OD280OD315ofdilutedwines   Proline
-1                 2.490725  458.2319
-2                 3.114043 1195.1489
+1                 3.114043 1195.1489
+2                 2.490725  458.2319
 3                 2.365484  728.3387
 
 Clustering vector:
-  [1] 2 2 2 2 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 2 2 3 3 2 2 3 2 2 2 2 2 2 3 3
- [38] 2 2 3 3 2 2 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 3 1 3 1 1 3 1 1 3 3 3 1 1 2
- [75] 3 1 1 1 3 1 1 3 3 1 1 1 1 1 3 3 1 1 1 1 1 3 3 1 3 1 3 1 1 1 3 1 1 1 1 3 1
-[112] 1 3 1 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 3 1 1 3 3 3 3 1 1 1 3 3 1 1 3 3 1 3
-[149] 3 1 1 1 1 3 3 3 1 3 3 3 1 3 1 3 3 1 3 3 3 3 1 1 3 3 3 3 3 1
+  [1] 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 3 3 3 1 1 3 3 1 1 3 1 1 1 1 1 1 3 3
+ [38] 1 1 3 3 1 1 3 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 3 2 3 2 2 3 2 2 3 3 3 2 2 1
+ [75] 3 2 2 2 3 2 2 3 3 2 2 2 2 2 3 3 2 2 2 2 2 3 3 2 3 2 3 2 2 2 3 2 2 2 2 3 2
+[112] 2 3 2 2 2 2 2 2 2 3 2 2 2 2 2 2 2 2 2 3 2 2 3 3 3 3 2 2 2 3 3 2 2 3 3 2 3
+[149] 3 2 2 2 2 3 3 3 2 3 3 3 2 3 2 3 3 2 3 3 3 3 2 2 3 3 3 3 3 2
 
 Within cluster sum of squares by cluster:
-[1]  443166.7 1360950.5  566572.5
+[1] 1360950.5  443166.7  566572.5
  (between_SS / total_SS =  86.5 %)
 
 Available components:
@@ -188,8 +188,8 @@ table()
 ``` output
      true
 quess  1  2  3
-    1  0 50 19
-    2 46  1  0
+    1 46  1  0
+    2  0 50 19
     3 13 20 29
 ```
 

diff --git a/md5sum.txt b/md5sum.txt
@@ -32,7 +32,7 @@
 "instructors/instructor-notes.md" "5cf113fd22defb29d17b64597f3c9bc0" "site/built/instructor-notes.md" "2024-11-18"
 "learners/CLT-dk.md" "a1852fcb44235823d23cd4a4af6d3d49" "site/built/CLT-dk.md" "2024-11-18"
 "learners/CLT-en.md" "8ae8f14f05472820ef155acf980ae06f" "site/built/CLT-en.md" "2024-11-18"
-"learners/data.md" "a799550e12471f2a4ed355fa1148d495" "site/built/data.md" "2024-11-18"
+"learners/data.md" "a959b4ea4bf7c39736330deb4eaa59ed" "site/built/data.md" "2024-11-18"
 "learners/reference.md" "527a12e217602daae51c5fd9ef8958df" "site/built/reference.md" "2024-11-18"
 "learners/setup.md" "9b1b924cf88e06b154562a92250fcb76" "site/built/setup.md" "2024-11-18"
 "poster/poster_dk.Rmd" "721a2b68eeb0b61308158bce41c6ae21" "site/built/poster_dk.md" "2024-11-18"

diff --git a/normal-distribution.md b/normal-distribution.md
@@ -196,7 +196,7 @@ rnorm(5, mean = 0, sd = 1 )
 ```
 
 ``` output
-[1] -0.3216684  1.4310444 -0.5655180 -1.3542069 -0.5022838
+[1] -1.12614700 -0.55713504 -1.30091311  0.04535995 -0.41484007
 ```
 Den returnerer (her) fem tilfældige værdier fra en normalfordeling med (her) 
 middelværdi 0 og standardafvigelse 1.