4.1 Explain AI’s Role in Exploratory Data Analysis (EDA) AI-TECHNICAL-PRACTITIONER Practice Questions (Page 7)

Questions 31–33

1. 31application · medium

   A research team is exploring a large genomic dataset and wants to generate hypotheses about which genes are associated with a disease. The team plans to use AI to support this exploration. What is the most effective way to use AI in this EDA phase?

   • AUse AI to replace all missing gene values with zeros to simplify the analysis.
   • BUse AI to generate a single hypothesis and stop after testing it once.
   • CUse AI to automatically conclude which genes cause the disease without further validation.
   • DUse AI to identify patterns and correlations between genes and the disease, then validate the top hypotheses with statistical tests.
   Reveal Solution Discussion Select an answer first
2. 32foundation · easy

   Why is human oversight important when using AI in EDA?

   • ATo manually perform all data cleaning tasks
   • BTo replace AI algorithms with manual analysis
   • CTo ensure AI never makes mistakes
   • DTo interpret results and catch potential biases or errors
   Reveal Solution Discussion Select an answer first
3. 33application · medium

   A marketing team has a customer dataset with dozens of behavioral and demographic features. They want to identify which features are most associated with high customer lifetime value to guide future campaigns. An AI tool is used to explore the data. Which outcome best represents AI's role in this EDA task?

   • AThe tool replaces all categorical variables with random numbers to enable numerical analysis.
   • BThe tool automatically generates a correlation matrix and ranks features by their statistical association with customer lifetime value.
   • CThe tool cleans the data by removing all rows with missing values, assuming they are irrelevant.
   • DThe tool creates a single scatter plot of customer age versus income for the entire dataset.
   Reveal Solution Discussion Select an answer first