Data Analysis & Reporting Flashcards
7 cards from real AML practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Data Analysis & Reporting flashcards as text
Which technique is used to reduce dimensionality while preserving the maximum variance in the data?
Answer: Principal Component Analysis (PCA)
PCA projects data onto orthogonal components ordered by explained variance, maximally preserving variance in fewer dimensions.
A model's training loss continues to decrease while validation loss increases after epoch 20. What does this report?
Answer: Overfitting
Divergence between training and validation loss curves is the classic signature of overfitting — the model memorizes training data but fails to generalize.
In A/B testing analysis, what is the risk of running multiple comparisons without correction?
Answer: Inflated Type I error rate (false positives)
Each additional comparison increases the probability of at least one false positive; Bonferroni or FDR corrections control this inflated error rate.
What does SHAP (SHapley Additive exPlanations) provide in ML reporting?
Answer: Per-prediction, feature-level attributions explaining individual model outputs
SHAP values assign each feature a contribution to a specific prediction, enabling both local (per-instance) and global interpretability.
A report shows Mean Absolute Error (MAE) = 5 and Root Mean Squared Error (RMSE) = 15 for a regression model. What does this gap suggest?
Answer: There are significant outlier errors driving up RMSE
RMSE penalizes large errors more than MAE; a large MAE-RMSE gap signals that some predictions have very large errors (outliers in residuals).
Which method is best for handling missing values in a numeric feature when the missingness is not random (MNAR)?
Answer: Creating a binary missingness indicator and imputing with median
When missingness is not at random, creating an indicator flag for missing values preserves information about the missingness pattern itself.
In data reporting, what is the primary advantage of using a waterfall chart over a simple bar chart?
Answer: Clearly shows cumulative effect of sequential positive and negative changes
Waterfall charts decompose a total into sequential incremental contributions, making it ideal for reporting how components add to or subtract from a KPI.