Temporal Models DY0-001 Practice Questions (Page 4)

Questions 16–20

1. 16foundation · easy

   Which scenario is best suited for causal inference rather than time series analysis?

   • AForecasting electricity demand for the next week
   • BIdentifying the seasonal pattern in retail sales
   • CEstimating the trend in global temperatures over the past century
   • DDetermining whether a new drug reduces blood pressure
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2. 17application · medium

   A pharmaceutical company is analyzing data from a clinical trial where patients are followed until they experience a side effect. The company also wants to determine whether the drug actually causes the side effect, rather than it occurring by chance. Which combination of analyses is most appropriate?

   • ASurvival analysis to estimate time-to-side-effect, and causal inference to assess the drug's effect
   • BTime series analysis for both the time-to-event data and the causal effect
   • CSurvival analysis only, since it can also establish causation
   • DCausal inference only, since it can handle censored time-to-event data
   Reveal Solution Discussion Select an answer first
4. 18application · medium

   A social scientist is studying the time until unemployed individuals find a new job. They also want to know whether participating in a job training program actually causes faster re-employment. The study is observational, and participants self-select into the program. Which combination of analyses is most appropriate?

   • ASurvival analysis only, since it can also establish causation
   • BTime series analysis for both the time-to-event data and the causal effect
   • CCausal inference only, since it can handle censored time-to-event data
   • DSurvival analysis for time-to-reemployment and causal inference methods to estimate the program's effect
   Reveal Solution Discussion Select an answer first
5. 19foundation · easy

   Which of the following is a common method used to control for confounding variables in observational studies?

   • ARandomization
   • BStratification
   • CPlacebo control
   • DBlinding
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6. 20foundation · easy

   What is the primary difference between the objectives of time series analysis and survival analysis?

   • ATime series analysis focuses on forecasting future values, while survival analysis focuses on estimating the time until an event
   • BTime series analysis is non-parametric, while survival analysis is parametric
   • CTime series analysis is used for causal inference, while survival analysis is used for prediction
   • DTime series analysis requires censored data, while survival analysis does not
   Reveal Solution Discussion Select an answer first