Q4 (20): Compute the clusters for the following normalized data (Age and Income) using hierarchical agglomerative clustering (using Average Linkage Rule and Manhattan Distance function). Please show all the steps Row ID Age (years) Income (thousand riyals per month) A 0.2 1 B 1 0.6 C 0.2 0.8 D 0.3 0.7 E 0.9 0.8 Table 3 Dissimilarity Matrix: 0 0 0 0 0 Clusters= + Dissimilarity Matrix: 0 0 0 0 Clusters= Dissimilarity Matrix: 0 0 0 Clusters= show the resulting clusters using a dendogram.
Added by Brian R.
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To calculate the Manhattan distance, we use the formula: Manhattan distance = |x1 - x2| + |y1 - y2| For example, the Manhattan distance between data points A and B is: |0.2 - 1| + |1 - 0.6| = 0.8 Similarly, we can calculate the Manhattan distance between all Show more…
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Scenario 2 This is the bivariate correlation matrix for the four variables (I-RiSC score, problem solving score, age in years, and annual income in dollars) for the sample of 20 people employed in the same industry. Answer each question by selecting all of the cells that apply. Click Submit to see if you found all of the correct ones. Question: In which cell(s) is the correlation between Problem Solving and Age shown?
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