In which scenarios would the distinction between continuous and discrete data become crucial?
- All scenarios
- When cleaning the data
- When developing a regression model
- When selecting a data visualization technique
The distinction between continuous and discrete data becomes crucial when developing regression models, as different models may be suitable depending on whether the data is continuous or discrete. For instance, linear regression is used for continuous data, while logistic regression is used for discrete data.
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