AN 300 UKY Exam #2 With Complete A
Cluster canalysis cis ca c__________________ ctechnique c- cCORRECT cANS✔✔Descriptive canalyt
Cluster canalysis cis cused cto cdiscover c- cCORRECT cANS✔✔Natural cgroupings cof cobjects
Cluster canalysis cis cused cto canswer cwhat c________________ cquestions c- cCORRECT cANS✔✔
Characteristics cof ccluster canalysis cproblems c- cCORRECT cANS✔✔- cThe cdata cthat cdescribes ct
- cIt cis cabout chow cto corganize cobjects cinto cgroups
- cIts cobjective cis cto cmaximize csimilarities cof cobjects cwithin cgroups
You chave cdata con cthe cweight cand cheight cof cpatients. cWhich csimilarity cmeasure cshould cbe cus
cgroup cof cpatients cis cto cone canother? c- cCORRECT cANS✔✔Euclidean
You chave cdata con cthe cgender cand cincome clevels cof ccustomers. cWhich csimilarity cmeasure csh
csimilar ca cgroup cof ccustomers cis cto cone canother? c- cCORRECT cANS✔✔Matching ccoefficient
It cis cthe clength cof ca cstraight cline cbetween ctwo cobjects. c- cCORRECT cANS✔✔Euclidean
It crequires creplacing cthe craw cvalue cof cdata cwith cits cz-score. c- cCORRECT cANS✔✔Euclidean
The clower cthe cmeasure cthe cbetter. c- cCORRECT cANS✔✔Euclidean
It cis cfor ccategorical cdata. c- cCORRECT cANS✔✔Matching ccoefficient
It cis ca cratio cof cnumber cof ccolumns cwith cmatching ccategorical cvalues cto cthe ctotal cnumber cof cc
cCORRECT cANS✔✔Matching ccoefficient
Business capplications cfor ccluster canalysis c- cCORRECT cANS✔✔- cDivide ccustomers cinto chomo
cMARKETING
- cDivide cclients cinto chomogenous cgroups cfor cpersonalized cFINANCIAL cadvice
- cIdentify coutliers cfor cquality ccontrol c(OPERATIONS)
Distance cbased ccluster canalysis cmethods... c- cCORRECT cANS✔✔Hierarchical cclustering cand ck
You chave c300 crows cof cdata. c- cCORRECT cANS✔✔Hierarchical
You conly chave cnumerical cdata cto cwork cwith. c- cCORRECT cANS✔✔K-Means
Cluster canalysis cis ca c__________________ ctechnique c- cCORRECT cANS✔✔Descriptive canalyt
Cluster canalysis cis cused cto cdiscover c- cCORRECT cANS✔✔Natural cgroupings cof cobjects
Cluster canalysis cis cused cto canswer cwhat c________________ cquestions c- cCORRECT cANS✔✔
Characteristics cof ccluster canalysis cproblems c- cCORRECT cANS✔✔- cThe cdata cthat cdescribes ct
- cIt cis cabout chow cto corganize cobjects cinto cgroups
- cIts cobjective cis cto cmaximize csimilarities cof cobjects cwithin cgroups
You chave cdata con cthe cweight cand cheight cof cpatients. cWhich csimilarity cmeasure cshould cbe cus
cgroup cof cpatients cis cto cone canother? c- cCORRECT cANS✔✔Euclidean
You chave cdata con cthe cgender cand cincome clevels cof ccustomers. cWhich csimilarity cmeasure csh
csimilar ca cgroup cof ccustomers cis cto cone canother? c- cCORRECT cANS✔✔Matching ccoefficient
It cis cthe clength cof ca cstraight cline cbetween ctwo cobjects. c- cCORRECT cANS✔✔Euclidean
It crequires creplacing cthe craw cvalue cof cdata cwith cits cz-score. c- cCORRECT cANS✔✔Euclidean
The clower cthe cmeasure cthe cbetter. c- cCORRECT cANS✔✔Euclidean
It cis cfor ccategorical cdata. c- cCORRECT cANS✔✔Matching ccoefficient
It cis ca cratio cof cnumber cof ccolumns cwith cmatching ccategorical cvalues cto cthe ctotal cnumber cof cc
cCORRECT cANS✔✔Matching ccoefficient
Business capplications cfor ccluster canalysis c- cCORRECT cANS✔✔- cDivide ccustomers cinto chomo
cMARKETING
- cDivide cclients cinto chomogenous cgroups cfor cpersonalized cFINANCIAL cadvice
- cIdentify coutliers cfor cquality ccontrol c(OPERATIONS)
Distance cbased ccluster canalysis cmethods... c- cCORRECT cANS✔✔Hierarchical cclustering cand ck
You chave c300 crows cof cdata. c- cCORRECT cANS✔✔Hierarchical
You conly chave cnumerical cdata cto cwork cwith. c- cCORRECT cANS✔✔K-Means
