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4 cards from this section. Quick, good the night before a test.
What is numerical data? Give an example.
Think about data that can be counted.
What is data acquisition?
It involves gathering information from various sources.
Which type of data consists of categories like color or gender?
Think about data that doesn’t involve counting.
Data processing is unnecessary for interpreting data.
Consider what happens if data is raw.
Consider a situation in which only categorical data is collected in a survey about technology preference. What are potential challenges in interpretation?
Reflect on how numeric ratings give more depth.
Predict what would happen if an AI model used unprocessed data directly without passing through data cleaning and transformation; provide reasoning.
Think about how errors impact overall results.
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