Quiz 5
Jacob Unkles
- Q1 Import data
- Q2 Review data
- Q3 Standardize data
- Q4 What is the standardization for?
- Q5 Find kmeans. What is kmeans for?
- Q6 Visualize clusters
- Q7 Summarize
- Q8 Hide the messages, but display the code and its results on the webpage.
- Q9 Display the title and your name correctly at the top of the webpage.
- Q10 Use the correct slug.
Replicate a case study of marketing analytics: https://www.linkedin.com/learning/the-data-science-of-marketing/cluster-analysis-with-r?u=2232593
Q1 Import data
myClusterData <- read.csv("cluster-r.csv")Q2 Review data
head(myClusterData)
## Email Behavior.3 Brand.Preference CTA
## 1 nisl@adipiscingelit.org 16 12 9
## 2 dui.Fusce.diam@non.edu 25 8 6
## 3 nisl.Maecenas@vitaeorciPhasellus.org 23 11 4
## 4 justo.nec@Aenean.edu 4 12 11
## 5 neque.Morbi.quis@AeneanmassaInteger.ca 29 10 2
## 6 elit@erat.org 16 6 13
## Demo.Age
## 1 48
## 2 41
## 3 50
## 4 34
## 5 59
## 6 57Q3 Standardize data
myClusterDataStandardized <- scale(myClusterData[-1])
myClusterDataStandardized
## Behavior.3 Brand.Preference CTA Demo.Age
## [1,] -0.06450461 1.5764994 -0.06016808 0.45191951
## [2,] 1.01724970 0.4409656 -0.65523704 0.02093360
## [3,] 0.77685986 1.2926159 -1.05194967 0.57505834
## [4,] -1.50684369 1.5764994 0.33654455 -0.41005230
## [5,] 1.49802940 1.0087325 -1.44866231 1.12918307
## [6,] -0.06450461 -0.1268013 0.73325719 1.00604424
## [7,] 1.13744463 0.1570822 -0.45688072 1.06761366
## [8,] -0.42508938 0.7248490 -1.05194967 1.43703015
## [9,] 0.77685986 1.0087325 0.53490087 1.06761366
## [10,] -0.66547923 -1.5462185 0.33654455 -1.08731587
## [11,] -1.02606400 -0.4106847 -0.25852440 -0.28691347
## [12,] 1.37783448 1.2926159 -0.85359335 -0.10220523
## [13,] -0.06450461 1.5764994 0.33654455 1.43703015
## [14,] 1.01724970 0.7248490 -0.45688072 -1.64144060
## [15,] 0.17588524 -0.1268013 -0.06016808 -0.41005230
## [16,] 0.65666493 0.1570822 1.32832614 1.12918307
## [17,] -1.38664877 0.4409656 1.32832614 -0.90260762
## [18,] -0.78567415 0.7248490 1.12996982 0.02093360
## [19,] 0.53647001 -1.5462185 1.32832614 -0.90260762
## [20,] -1.50684369 -0.6945681 -0.45688072 -0.10220523
## [21,] 1.61822432 -0.4106847 1.52668246 -0.96417704
## [22,] 1.01724970 1.5764994 -0.85359335 -1.70301002
## [23,] 0.17588524 -0.9784516 -0.85359335 1.43703015
## [24,] 0.77685986 -0.9784516 -1.64701862 0.57505834
## [25,] 0.65666493 -0.1268013 -0.25852440 0.39035009
## [26,] -1.74723354 1.0087325 -1.05194967 0.45191951
## [27,] 1.49802940 -1.2623350 -1.64701862 0.69819717
## [28,] 0.65666493 1.2926159 -0.85359335 -0.47162172
## [29,] -1.38664877 -1.2623350 -1.44866231 -1.21045470
## [30,] 0.53647001 0.1570822 -1.44866231 -0.16377464
## [31,] -0.42508938 -0.6945681 0.53490087 -1.21045470
## [32,] -0.42508938 -1.5462185 -1.25030599 -0.65632996
## [33,] 1.61822432 1.0087325 -1.05194967 1.31389132
## [34,] 1.61822432 -0.6945681 -0.85359335 -1.57987119
## [35,] -0.30489446 -1.5462185 -0.25852440 1.56016898
## [36,] -0.18469953 -0.6945681 0.73325719 -1.39516294
## [37,] 1.61822432 0.7248490 0.93161350 1.06761366
## [38,] -0.06450461 -1.2623350 -0.25852440 1.06761366
## [39,] -0.54528430 -1.2623350 1.72503878 -0.84103821
## [40,] 1.01724970 -0.1268013 0.53490087 0.45191951
## [41,] 0.05569031 0.4409656 -0.45688072 -0.41005230
## [42,] 0.53647001 1.5764994 -1.25030599 -0.22534406
## [43,] -1.62703862 1.2926159 -0.06016808 -1.08731587
## [44,] -1.02606400 1.0087325 0.93161350 -0.34848289
## [45,] -0.06450461 1.5764994 1.12996982 -1.45673236
## [46,] -1.74723354 -0.9784516 -0.65523704 1.62173839
## [47,] 0.77685986 -1.2623350 -0.45688072 -0.84103821
## [48,] 1.37783448 -0.4106847 -0.06016808 0.94447483
## [49,] -0.42508938 -1.2623350 1.32832614 0.75976658
## [50,] -1.38664877 -0.1268013 -1.44866231 1.31389132
## [51,] -0.66547923 -0.6945681 0.53490087 0.08250302
## [52,] -0.18469953 -1.2623350 -1.05194967 1.06761366
## [53,] -0.54528430 1.5764994 0.93161350 0.14407243
## [54,] 0.29608016 -0.4106847 -0.85359335 -0.22534406
## [55,] 1.01724970 0.4409656 -1.64701862 -0.90260762
## [56,] 1.37783448 0.4409656 -0.65523704 -0.77946879
## [57,] -0.30489446 0.7248490 -1.64701862 0.39035009
## [58,] -0.78567415 -0.6945681 0.93161350 -0.77946879
## [59,] 0.89705478 0.7248490 1.72503878 0.82133600
## [60,] 1.61822432 0.1570822 0.73325719 0.32878068
## [61,] -0.78567415 1.2926159 0.93161350 1.12918307
## [62,] 1.01724970 -0.6945681 -0.85359335 -0.71789938
## [63,] 0.29608016 -1.2623350 -1.25030599 -0.16377464
## [64,] -0.18469953 1.5764994 1.72503878 -1.27202411
## [65,] -1.14625892 0.7248490 -1.05194967 1.31389132
## [66,] -1.50684369 0.7248490 0.73325719 -0.22534406
## [67,] 0.41627509 -0.4106847 -1.64701862 -0.96417704
## [68,] -1.26645385 -1.5462185 -0.06016808 -1.14888528
## [69,] 1.01724970 0.7248490 -0.65523704 -1.64144060
## [70,] -1.38664877 -0.4106847 -1.44866231 -0.34848289
## [71,] 0.53647001 -1.5462185 0.73325719 1.37546073
## [72,] 0.29608016 0.4409656 0.93161350 -1.27202411
## [73,] 0.29608016 -0.6945681 0.73325719 0.82133600
## [74,] -0.42508938 0.4409656 1.32832614 0.57505834
## [75,] -0.30489446 1.5764994 -1.25030599 0.51348892
## [76,] -0.42508938 1.0087325 -0.06016808 -0.53319113
## [77,] -1.50684369 -0.1268013 1.12996982 0.14407243
## [78,] 1.01724970 1.0087325 -0.85359335 -0.28691347
## [79,] 1.61822432 -0.6945681 1.72503878 -0.10220523
## [80,] 1.61822432 -0.9784516 1.12996982 0.39035009
## [81,] -0.66547923 0.4409656 -0.25852440 0.94447483
## [82,] -1.38664877 1.0087325 1.72503878 -0.34848289
## [83,] -1.62703862 1.2926159 -0.85359335 -0.28691347
## [84,] 0.05569031 -0.1268013 0.93161350 -0.53319113
## [85,] 1.49802940 -0.6945681 0.33654455 0.45191951
## [86,] -0.06450461 1.5764994 -1.64701862 1.06761366
## [87,] 1.25763955 -0.9784516 -0.45688072 -0.59476055
## [88,] 1.01724970 -0.9784516 -0.65523704 0.08250302
## [89,] 0.05569031 1.5764994 0.33654455 0.08250302
## [90,] -1.14625892 -0.9784516 -0.06016808 1.19075249
## [91,] 1.13744463 1.5764994 -1.05194967 1.25232190
## [92,] -1.02606400 -0.9784516 0.93161350 1.12918307
## [93,] 1.13744463 -1.5462185 -1.25030599 -1.70301002
## [94,] -0.42508938 -1.2623350 -1.05194967 0.94447483
## [95,] -1.26645385 0.1570822 0.53490087 1.25232190
## [96,] 0.89705478 1.0087325 -0.85359335 1.25232190
## [97,] -0.42508938 -0.4106847 1.12996982 1.49859956
## [98,] -1.50684369 -1.5462185 -1.05194967 0.75976658
## [99,] -0.30489446 -0.1268013 1.52668246 -0.96417704
## [100,] -0.18469953 1.2926159 1.72503878 -0.59476055
## [101,] 0.29608016 -1.2623350 -1.25030599 -1.33359353
## [102,] -1.38664877 -1.5462185 -0.85359335 -1.51830177
## [103,] -0.90586907 -0.4106847 1.52668246 -0.90260762
## [104,] -0.90586907 1.2926159 -0.85359335 1.19075249
## [105,] 0.53647001 -0.9784516 1.12996982 0.88290541
## [106,] 0.53647001 -1.5462185 -0.65523704 1.68330781
## [107,] -0.78567415 1.5764994 -0.06016808 0.63662775
## [108,] 0.65666493 0.4409656 -1.64701862 -0.90260762
## [109,] -0.78567415 -1.2623350 -1.25030599 1.49859956
## [110,] -0.06450461 -0.6945681 -0.65523704 -0.96417704
## [111,] 0.41627509 -0.1268013 -0.85359335 1.12918307
## [112,] -0.78567415 0.4409656 -0.06016808 0.26721126
## [113,] -1.74723354 -1.2623350 0.33654455 -1.45673236
## [114,] 1.61822432 -0.4106847 0.13818823 0.75976658
## [115,] -1.38664877 -0.1268013 -0.25852440 1.25232190
## [116,] -1.26645385 -0.1268013 1.72503878 -0.90260762
## [117,] -1.02606400 0.4409656 -1.64701862 0.02093360
## [118,] -0.54528430 1.5764994 1.32832614 -0.04063581
## [119,] 0.05569031 1.5764994 0.33654455 0.02093360
## [120,] -0.66547923 -0.4106847 -1.64701862 -1.08731587
## [121,] -0.18469953 1.2926159 0.53490087 1.68330781
## [122,] -1.02606400 0.4409656 1.32832614 -0.90260762
## [123,] -1.86742846 0.4409656 1.52668246 -0.22534406
## [124,] 0.77685986 0.7248490 1.32832614 -0.04063581
## [125,] 1.25763955 -1.2623350 0.73325719 -0.53319113
## [126,] 1.13744463 -0.4106847 1.12996982 -1.14888528
## [127,] -0.42508938 -1.5462185 0.13818823 -1.08731587
## [128,] -0.90586907 0.7248490 -0.65523704 -0.34848289
## [129,] 1.13744463 1.2926159 0.33654455 0.32878068
## [130,] 0.89705478 -0.1268013 1.12996982 0.39035009
## [131,] 0.29608016 0.4409656 -0.85359335 1.62173839
## [132,] -0.54528430 0.1570822 0.13818823 1.37546073
## [133,] -0.90586907 -0.9784516 -0.25852440 0.75976658
## [134,] 1.37783448 -1.5462185 -1.25030599 0.88290541
## [135,] 1.25763955 0.7248490 0.13818823 -0.65632996
## [136,] 0.29608016 -0.9784516 1.32832614 0.88290541
## [137,] 0.41627509 -0.1268013 1.72503878 0.82133600
## [138,] 1.01724970 -1.5462185 -0.85359335 -1.08731587
## [139,] 0.65666493 -0.4106847 0.33654455 1.06761366
## [140,] 1.25763955 0.1570822 1.12996982 1.62173839
## [141,] 0.53647001 -1.2623350 -0.06016808 -1.21045470
## [142,] 0.17588524 1.5764994 1.52668246 -1.45673236
## [143,] -1.50684369 0.7248490 0.53490087 -1.21045470
## [144,] -0.06450461 1.2926159 0.93161350 0.08250302
## [145,] -0.78567415 1.5764994 -0.25852440 -0.59476055
## [146,] -0.42508938 -0.1268013 1.72503878 -1.21045470
## [147,] -0.66547923 -0.1268013 1.52668246 -1.45673236
## [148,] -1.86742846 1.2926159 1.32832614 1.31389132
## [149,] -0.42508938 1.2926159 0.53490087 -1.02574645
## [150,] -1.02606400 -1.2623350 0.53490087 0.39035009
## [151,] 1.61822432 1.2926159 0.73325719 -0.22534406
## [152,] 0.65666493 1.5764994 0.13818823 -1.27202411
## [153,] -0.18469953 -0.1268013 0.33654455 -0.65632996
## [154,] 0.41627509 0.4409656 -0.45688072 -0.34848289
## [155,] 1.13744463 1.0087325 -1.05194967 -0.28691347
## [156,] -0.18469953 0.4409656 -1.05194967 -1.14888528
## [157,] 1.01724970 -1.5462185 -0.65523704 1.56016898
## [158,] -1.86742846 -0.1268013 -0.65523704 -0.90260762
## [159,] -0.54528430 0.1570822 0.73325719 0.26721126
## [160,] 0.17588524 -1.5462185 -1.25030599 0.32878068
## [161,] -1.62703862 1.5764994 -1.64701862 -0.84103821
## [162,] -1.62703862 0.4409656 -0.25852440 1.19075249
## [163,] -1.50684369 0.1570822 -1.44866231 -0.59476055
## [164,] -1.50684369 -0.9784516 0.33654455 -0.04063581
## [165,] -0.90586907 -0.6945681 0.73325719 -1.64144060
## [166,] -1.38664877 1.5764994 -0.65523704 -1.33359353
## [167,] -0.90586907 -0.6945681 0.93161350 0.45191951
## [168,] -1.62703862 -0.4106847 -1.64701862 -1.14888528
## [169,] 0.77685986 -0.6945681 0.73325719 -1.57987119
## [170,] 0.29608016 0.7248490 -1.64701862 -0.59476055
## [171,] 1.13744463 -0.4106847 0.73325719 -0.41005230
## [172,] -0.42508938 -1.2623350 1.12996982 -1.39516294
## [173,] -0.54528430 -0.4106847 -1.25030599 1.31389132
## [174,] 1.01724970 -1.5462185 -0.25852440 -1.64144060
## [175,] -0.78567415 -1.2623350 0.93161350 1.56016898
## [176,] -1.50684369 -0.9784516 -0.25852440 -1.21045470
## [177,] 1.49802940 -0.6945681 1.32832614 0.32878068
## [178,] 0.29608016 0.1570822 -0.45688072 0.69819717
## [179,] -0.66547923 0.1570822 0.93161350 1.12918307
## [180,] -0.78567415 0.4409656 -0.45688072 -0.90260762
## [181,] 1.13744463 -0.4106847 -1.25030599 1.06761366
## [182,] -0.66547923 0.4409656 -1.25030599 -0.53319113
## [183,] -1.14625892 -0.1268013 0.53490087 -0.28691347
## [184,] 0.29608016 -0.9784516 -1.44866231 0.45191951
## [185,] 0.41627509 -1.5462185 -0.85359335 -0.65632996
## [186,] 0.05569031 0.4409656 1.72503878 -0.28691347
## [187,] 1.13744463 -0.9784516 0.33654455 -0.96417704
## [188,] -0.06450461 -1.2623350 0.33654455 0.88290541
## [189,] 1.13744463 1.2926159 0.93161350 -1.21045470
## [190,] -1.14625892 -0.1268013 -0.06016808 -1.39516294
## [191,] -1.74723354 -1.5462185 0.73325719 -0.04063581
## [192,] -1.38664877 -0.9784516 1.12996982 -1.51830177
## [193,] 1.61822432 -0.1268013 0.33654455 1.19075249
## [194,] -0.06450461 -0.6945681 0.33654455 1.31389132
## [195,] 0.17588524 -0.6945681 -0.06016808 1.19075249
## [196,] -1.62703862 1.0087325 1.12996982 -1.33359353
## [197,] 1.49802940 0.7248490 -0.85359335 0.02093360
## [198,] 1.61822432 0.1570822 0.73325719 -1.27202411
## [199,] 0.53647001 -0.4106847 -1.05194967 1.25232190
## [200,] -0.18469953 -0.4106847 -0.85359335 -0.59476055
## [201,] -1.14625892 1.0087325 0.73325719 -0.22534406
## [202,] 0.53647001 0.1570822 -1.05194967 -0.28691347
## [203,] 0.41627509 1.5764994 -1.64701862 0.94447483
## [204,] 1.37783448 0.7248490 1.52668246 -1.02574645
## [205,] -0.18469953 1.0087325 -0.06016808 -0.10220523
## [206,] 1.13744463 1.5764994 1.12996982 0.39035009
## [207,] 1.37783448 -0.6945681 -1.64701862 0.14407243
## [208,] -0.78567415 -0.4106847 0.53490087 1.19075249
## [209,] 0.29608016 0.4409656 -0.25852440 0.39035009
## [210,] 0.17588524 -0.9784516 -0.45688072 -1.64144060
## [211,] 1.61822432 1.2926159 -0.25852440 -1.33359353
## [212,] -0.18469953 -1.2623350 -0.85359335 0.02093360
## [213,] 0.17588524 0.4409656 1.32832614 -1.70301002
## [214,] 0.89705478 1.5764994 -0.45688072 -0.34848289
## [215,] 1.37783448 0.1570822 0.93161350 0.82133600
## [216,] -0.66547923 -1.5462185 0.13818823 0.14407243
## [217,] -1.38664877 1.2926159 0.13818823 -1.02574645
## [218,] 1.25763955 0.1570822 -0.65523704 -0.53319113
## [219,] 0.17588524 -0.1268013 0.93161350 -1.39516294
## [220,] 0.77685986 -1.2623350 -1.44866231 0.88290541
## [221,] 1.13744463 1.2926159 -0.06016808 1.19075249
## [222,] -0.90586907 -0.9784516 -1.05194967 1.68330781
## [223,] -1.26645385 -1.5462185 -1.05194967 -0.10220523
## [224,] 0.53647001 -0.1268013 -0.45688072 0.14407243
## [225,] -0.42508938 -0.1268013 -1.44866231 -0.41005230
## [226,] 0.17588524 -0.4106847 -0.65523704 -1.02574645
## [227,] -0.06450461 1.0087325 -1.25030599 -1.51830177
## [228,] -0.06450461 0.1570822 -0.25852440 -0.96417704
## [229,] 1.49802940 1.0087325 -1.44866231 -0.22534406
## [230,] -1.50684369 0.7248490 0.33654455 0.39035009
## [231,] -1.26645385 -0.1268013 0.93161350 1.31389132
## [232,] -1.14625892 0.7248490 0.33654455 -1.45673236
## [233,] -1.14625892 -0.4106847 -0.06016808 0.75976658
## [234,] -0.42508938 1.2926159 1.72503878 -1.51830177
## [235,] -0.78567415 -1.5462185 0.53490087 1.68330781
## [236,] -0.66547923 -1.2623350 1.12996982 0.75976658
## [237,] -1.02606400 -0.1268013 0.93161350 0.26721126
## [238,] 1.37783448 -1.2623350 1.32832614 -0.65632996
## [239,] 1.25763955 0.7248490 1.52668246 1.31389132
## [240,] 0.17588524 -1.2623350 0.13818823 1.49859956
## [241,] -0.18469953 -0.1268013 0.93161350 0.08250302
## [242,] 0.53647001 0.4409656 1.12996982 1.43703015
## [243,] -0.90586907 -0.9784516 -0.25852440 -0.77946879
## [244,] 1.13744463 0.1570822 -1.44866231 1.37546073
## [245,] 0.89705478 -0.4106847 1.52668246 0.75976658
## [246,] -0.90586907 -1.5462185 -1.25030599 1.06761366
## [247,] 1.61822432 1.2926159 -1.05194967 -0.28691347
## [248,] -0.54528430 0.4409656 -1.25030599 -1.21045470
## [249,] -0.30489446 0.7248490 -0.65523704 -1.39516294
## [250,] -0.42508938 1.5764994 0.93161350 1.00604424
## [251,] 0.05569031 -1.5462185 -0.85359335 -0.16377464
## [252,] 1.37783448 0.1570822 1.52668246 0.82133600
## [253,] 1.49802940 -1.5462185 0.53490087 0.82133600
## [254,] -1.86742846 0.4409656 -0.85359335 1.37546073
## [255,] 1.25763955 -1.2623350 -1.25030599 1.37546073
## [256,] -1.62703862 -1.5462185 0.93161350 -1.27202411
## [257,] 1.13744463 -0.6945681 -1.25030599 0.57505834
## [258,] -1.38664877 0.1570822 -0.65523704 0.08250302
## [259,] -0.54528430 1.2926159 1.32832614 -0.04063581
## [260,] 0.41627509 -0.1268013 0.93161350 0.82133600
## [261,] 1.37783448 -1.2623350 -0.25852440 -0.59476055
## [262,] 1.01724970 0.4409656 -0.25852440 0.39035009
## [263,] 0.65666493 -1.5462185 1.52668246 1.12918307
## [264,] -0.06450461 1.2926159 -1.05194967 -0.47162172
## [265,] 1.37783448 -0.4106847 0.13818823 0.02093360
## [266,] 1.01724970 1.0087325 0.33654455 1.43703015
## [267,] 0.41627509 1.0087325 1.52668246 -1.45673236
## [268,] 0.89705478 1.2926159 1.32832614 -1.27202411
## [269,] 1.25763955 -0.6945681 -0.65523704 -1.02574645
## [270,] 0.53647001 -0.1268013 -1.44866231 -0.59476055
## [271,] -0.06450461 -0.6945681 -0.45688072 -1.64144060
## [272,] 1.13744463 1.0087325 1.32832614 0.88290541
## [273,] -1.02606400 0.7248490 0.73325719 1.68330781
## [274,] 0.53647001 -0.9784516 -0.25852440 -0.28691347
## [275,] -1.02606400 -0.1268013 1.12996982 0.45191951
## [276,] -1.74723354 -0.1268013 1.32832614 -1.70301002
## [277,] -0.54528430 1.2926159 0.33654455 -0.28691347
## [278,] 0.29608016 -0.1268013 -0.45688072 1.56016898
## [279,] 1.25763955 -0.6945681 -0.25852440 1.19075249
## [280,] 0.05569031 -0.9784516 -1.25030599 -1.08731587
## [281,] -1.02606400 1.5764994 -1.05194967 1.12918307
## [282,] 0.89705478 -1.5462185 -0.85359335 0.51348892
## [283,] 1.61822432 1.2926159 -1.25030599 0.20564185
## [284,] 0.41627509 -0.4106847 0.73325719 -1.70301002
## [285,] -1.02606400 -0.9784516 0.13818823 -1.14888528
## [286,] -0.78567415 -0.6945681 -0.06016808 -1.21045470
## [287,] 1.13744463 -1.2623350 1.12996982 1.62173839
## [288,] 0.05569031 -1.5462185 1.32832614 -0.22534406
## [289,] -1.50684369 0.7248490 1.52668246 -1.70301002
## [290,] 0.29608016 1.0087325 -0.85359335 1.62173839
## [291,] -0.90586907 1.0087325 -0.45688072 1.56016898
## [292,] -1.26645385 1.2926159 -0.06016808 -0.53319113
## [293,] -1.14625892 1.5764994 0.73325719 -0.04063581
## [294,] 1.49802940 0.1570822 1.52668246 0.20564185
## [295,] 0.05569031 1.5764994 -1.05194967 1.43703015
## [296,] 1.25763955 1.2926159 -1.05194967 -0.47162172
## [297,] 0.53647001 1.2926159 0.13818823 0.57505834
## [298,] -1.02606400 0.1570822 -1.25030599 0.32878068
## [299,] 0.17588524 -1.2623350 -1.05194967 -1.33359353
## [300,] 0.05569031 -0.9784516 -0.65523704 1.56016898
## attr(,"scaled:center")
## Behavior.3 Brand.Preference CTA Demo.Age
## 16.536667 6.446667 9.303333 40.660000
## attr(,"scaled:scale")
## Behavior.3 Brand.Preference CTA Demo.Age
## 8.319819 3.522573 5.041433 16.241830Q4 What is the standardization for?
The standardization is to normalize the data, which means that the values of the variables are all similar and based on a common mean of 1. The variables are standardized to give equal weight to all numeric variables.
Q5 Find kmeans. What is kmeans for?
ourGroups <- kmeans(myClusterDataStandardized, 3)
ourGroups
## K-means clustering with 3 clusters of sizes 98, 110, 92
##
## Cluster means:
## Behavior.3 Brand.Preference CTA Demo.Age
## 1 -0.6519880 0.24108849 0.7271851 -0.6864864
## 2 0.2021096 -0.09325141 0.1165494 1.0541803
## 3 0.4528561 -0.14531541 -0.9139627 -0.5291757
##
## Clustering vector:
## [1] 2 3 3 1 2 2 2 2 2 1 1 3 2 3 3 2 1 1 1 1 1 3 2 3 2 1 3 3 3 3 1 3 2 3 2 1 2
## [38] 2 1 2 3 3 1 1 1 2 3 2 2 2 1 2 1 3 3 3 3 1 2 2 2 3 3 1 2 1 3 1 3 3 2 1 2 1
## [75] 3 1 1 3 2 2 2 1 1 1 2 2 3 3 1 2 2 2 3 2 2 2 2 2 1 1 3 3 1 2 2 2 2 3 2 3 2
## [112] 1 1 2 2 1 3 1 1 3 2 1 1 1 3 1 1 1 2 2 2 2 2 3 3 2 2 3 2 2 3 1 1 1 1 1 1 1
## [149] 1 2 2 1 1 3 3 3 2 1 1 3 3 2 3 1 1 1 1 3 1 3 3 1 2 3 2 1 2 2 2 1 2 3 1 3 3
## [186] 1 3 2 1 1 1 1 2 2 2 1 3 3 2 3 1 3 3 1 1 2 3 2 2 3 3 3 1 3 2 2 1 3 1 3 2 2
## [223] 3 3 3 3 3 3 3 1 2 1 2 1 2 2 1 1 2 2 1 2 1 2 2 2 3 3 3 2 3 2 2 2 2 1 3 1 1
## [260] 2 3 2 2 3 3 2 1 1 3 3 3 2 2 3 1 1 1 2 2 3 2 3 3 1 1 1 2 1 1 2 2 1 1 2 2 3
## [297] 2 3 3 2
##
## Within cluster sum of squares by cluster:
## [1] 251.3690 316.8359 229.8251
## (between_SS / total_SS = 33.3 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"Q6 Visualize clusters
library(cluster)
clusplot(myClusterDataStandardized, ourGroups$cluster)
Q7 Summarize
ourGroups$size
## [1] 98 110 92