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CAP Methodology Selection & Analytics Problem Framing Flashcards

6 cards from real CAP practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

Read the first 6 CAP Methodology Selection & Analytics Problem Framing flashcards as text
  1. Which evaluation metric is MOST appropriate for a highly imbalanced binary classification problem?

    Answer: Area Under the ROC Curve (AUC-ROC)

    AUC-ROC evaluates discrimination ability across all thresholds and is robust to class imbalance, unlike accuracy.

  2. A CAP analyst must choose between a linear regression model and a decision tree for a continuous outcome. The BEST reason to prefer linear regression is:

    Answer: It provides easily interpretable coefficients for stakeholders

    Linear regression coefficients have clear directional interpretations, making results more communicable to non-technical stakeholders.

  3. Cross-validation is used during methodology selection primarily to:

    Answer: Estimate model performance on unseen data

    Cross-validation provides an unbiased estimate of how well the model will generalize by repeatedly testing on held-out data folds.

  4. When an analytics problem involves predicting the number of events in a fixed time interval, which model family is MOST appropriate?

    Answer: Poisson regression

    Poisson regression is designed for count outcomes representing events in a fixed time or space interval.

  5. Which concept describes selecting the simplest model that adequately explains the data?

    Answer: Parsimony

    Parsimony (Occam's Razor) favors simpler models to avoid overfitting and improve generalizability.

  6. A team debates using a neural network versus a linear model for a small dataset with 200 rows. The CAP best practice recommends:

    Answer: Use the simpler linear model to avoid overfitting

    Neural networks require large datasets to generalize; on small datasets a simpler linear model typically outperforms and avoids overfitting.

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