CAIC Data Analytics 2

Question 1

Which statistical technique is most appropriate for identifying hidden groupings in unlabeled customer data?

Accepted Answer

K-means clustering

Answer

K-means clustering is an unsupervised technique that partitions data into k groups based on feature similarity without requiring labels.

Question 2

An AI consultant is asked to evaluate model fairness. Which metric detects whether a model performs significantly worse for a protected demographic group?

Accepted Answer

Disparate impact ratio

Answer

Disparate impact ratio compares outcome rates across demographic groups and flags values below 0.8 as potentially discriminatory.

Question 3

What does a high variance but low bias in a predictive model typically indicate?

Accepted Answer

The model is overfitting

Answer

High variance and low bias indicates the model has learned noise in the training data and fails to generalize—a classic overfitting pattern.

Question 4

A data pipeline silently drops records with NULL values in a key field. What type of data quality issue does this represent?

Accepted Answer

Silent data loss

Answer

Silent data loss occurs when records are discarded without alerts or logging, making the issue invisible to downstream consumers.

Question 5

Which visualization type is best suited for showing the distribution and spread of a continuous numeric variable?

Accepted Answer

Box plot

Answer

A box plot displays the median, quartiles, and outliers of a continuous variable, making distribution and spread immediately visible.

(CAIC) Certified AI Consultant Practice Test

(CAIC) Certified AI Consultant Practice Test

CAIC Data Analytics 2