DA0-002 Data Analysis Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  5

  Why it's wrong here

  Choosing 5 follows the secondary bend, yet the elbow method selects the point of maximum curvature reduction, which occurs at k=3; the k=5 bend adds marginal within-cluster variance improvement. The method suits estimating k when no domain-defined cluster count exists, but here the sharp bend already answers it.

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  The method is inconclusive.

  Why it's wrong here

  The elbow method selects the point of maximum curvature, so the sharp bend at k=3 is the recommended cluster count; a small bend at k=5 does not override it. Calling the method inconclusive is tempting when bends are ambiguous or gradual, where silhouette scoring or gap statistics would be needed instead.

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  2

  Why it's wrong here

  The elbow method selects the k at the sharpest bend, where adding clusters stops yielding meaningful within-cluster variance reduction; k=2 sits before that point, underfitting the structure. Two clusters would be right only if the plot's clear bend occurred there.

• ✓

  3

  Why this is correct

  The elbow method selects the k where the within-cluster sum of squares drops sharply before levelling off. The sharp bend at k=3 marks that inflection point, so three clusters is recommended; the minor bend at k=5 is a secondary, weaker signal.