CTE Data Analytics 3

Question 1

Which visualization type is most effective for showing the distribution of call duration across millions of CDRs (Call Detail Records)?

Accepted Answer

Histogram with logarithmic y-axis

Answer

A histogram reveals the full shape of the distribution (skew, outliers, modes) across large datasets, which is critical for CDR analysis.

Question 2

A telecom executive wants to reduce customer churn. Which predictive modeling output is most operationally useful?

Accepted Answer

A ranked propensity-to-churn score per customer with associated confidence intervals

Answer

Individual propensity scores allow retention teams to prioritize outreach to the highest-risk customers before they churn.

Question 3

What does a Lorenz curve reveal when applied to telecom revenue data?

Accepted Answer

The degree of revenue concentration among the top percentage of customers

Answer

The Lorenz curve illustrates how much of total revenue is attributable to what share of the customer base, revealing revenue concentration (Gini coefficient).

Question 4

When building a telecom customer lifetime value (CLV) model, which input variable is typically the strongest predictor?

Accepted Answer

Historical payment behavior and plan tenure

Answer

Consistent payment history and long tenure directly indicate future revenue reliability and the customer's value horizon.

Question 5

A/B testing in telecom marketing requires which of the following to ensure valid results?

Accepted Answer

Random assignment of customers to control and treatment groups with sufficient sample size

Answer

Random assignment eliminates selection bias, and adequate sample size ensures the test has sufficient statistical power to detect real differences.

(CTE) Certified Telecommunications Executive Practice Test

(CTE) Certified Telecommunications Executive Practice Test

CTE Data Analytics 3