Web Traffic Research & Evidence-Based Practice 3

Question 1

An analyst notices that a competitor launched a major campaign on the same day as an internal SEO update. Which research concept describes this problem?

Accepted Answer

Confounding

Answer

Confounding occurs when a third variable (the competitor campaign) is associated with both the treatment and the outcome, making it impossible to isolate the SEO update's effect.

Question 2

When segmenting traffic data by device type for a research study, which sampling approach ensures proportional representation of mobile, desktop, and tablet users?

Accepted Answer

Stratified random sampling

Answer

Stratified random sampling divides the population into device-type strata and samples from each proportionally, ensuring all segments are adequately represented.

Question 3

A study reports that pages with longer dwell time rank higher in search results. What causal inference problem must researchers address before concluding dwell time improves rankings?

Accepted Answer

Reverse causality

Answer

Reverse causality is the problem that higher-ranking pages attract more engaged users, so dwell time may be a consequence of ranking rather than a cause.

Question 4

Which visualization is most effective for communicating the distribution of session durations across thousands of user visits in a research report?

Accepted Answer

Violin plot

Answer

A violin plot combines a box plot with a kernel density estimate, revealing the full shape of the session duration distribution including skewness and multimodal patterns.

Question 5

A researcher uses Google Analytics data to study user behavior. Which limitation must be disclosed when publishing findings?

Accepted Answer

GA sampling occurs for high-traffic reports, potentially biasing estimates

Answer

Google Analytics applies data sampling in standard reports for high-traffic properties, meaning reported metrics may not reflect all sessions, introducing bias.

Web Traffic Practice Test

Web Traffic Practice Test

Web Traffic Research & Evidence-Based Practice 3