Which type of data is survival analysis specifically designed to handle?

Data with censored observations

Data that is normally distributed

Data that is collected at equally spaced time intervals

A clinical researcher is studying the time until patients relapse after a new treatment. Some patients are still relapse-free at the end of the study, and others dropped out early. The researcher needs to estimate the probability of remaining relapse-free over time, accounting for these incomplete observations. Which method is most appropriate?

Linear regression on time to relapse

A city government wants to determine whether installing new traffic lights at intersections reduces accident rates. They have historical accident data from many intersections, some with new lights and some without. However, intersections with new lights tend to be in busier areas. The analyst must establish a causal effect, not just an association. Which approach is the most rigorous?

Compare average accident rates before and after installation at the same intersections

Conduct a randomized controlled trial by randomly assigning intersections to receive new lights or not

Use a time series forecast of accidents at each intersection

Calculate the correlation between the presence of new lights and accident rates

An economist wants to test whether a change in interest rates causes a change in housing prices. They have monthly data for both variables over 20 years. The data are non-stationary and may be cointegrated. Which approach is most appropriate to test for a causal relationship?

Granger causality test after ensuring stationarity and checking for cointegration

Simple correlation between interest rates and housing prices

Time series decomposition of housing prices alone

Survival analysis of housing price changes

CompTIADataX

Domain 1Objective 4

Temporal Models DY0-001 Practice Questions (Page 6)

Part of the Mathematics and statistics domain, which accounts for 17% of the DY0-001 exam. CompTIA does not publish an official question count, but from its 165-minute exam (~65–110 total, ~11–19 in this domain), expect 3–5 from this objective — we provide 34 practice questions to prepare you well beyond it. (estimate)

34questions here

7free pages

9concepts

17%of the exam

Questions 26–30

26foundation · easy
Which type of data is survival analysis specifically designed to handle?
Select an answer first
27application · medium
A clinical researcher is studying the time until patients relapse after a new treatment. Some patients are still relapse-free at the end of the study, and others dropped out early. The researcher needs to estimate the probability of remaining relapse-free over time, accounting for these incomplete observations. Which method is most appropriate?
Select an answer first
28application · medium
A city government wants to determine whether installing new traffic lights at intersections reduces accident rates. They have historical accident data from many intersections, some with new lights and some without. However, intersections with new lights tend to be in busier areas. The analyst must establish a causal effect, not just an association. Which approach is the most rigorous?
Select an answer first
29expert · hard
An economist wants to test whether a change in interest rates causes a change in housing prices. They have monthly data for both variables over 20 years. The data are non-stationary and may be cointegrated. Which approach is most appropriate to test for a causal relationship?
Select an answer first
30foundation · easy
Which technique is commonly used to compare survival curves between two or more groups?
Select an answer first

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Temporal Models DY0-001 Practice Questions (Page 6)

Questions 26–30

Which type of data is survival analysis specifically designed to handle?

An economist wants to test whether a change in interest rates causes a change in housing prices. They have monthly data for both variables over 20 years. The data are non-stationary and may be cointegrated. Which approach is most appropriate to test for a causal relationship?

Which technique is commonly used to compare survival curves between two or more groups?

Keep studying — Mathematics and statistics