Can you describe a scenario where you would need to handle missing values when calculating the mean in R?
- Analyzing survey data with missing responses
- Calculating the average sales per month with missing data for some months
- Working with a dataset that contains NA values
- All of the above
All of the mentioned scenarios may require handling missing values when calculating the mean in R. For example, when analyzing survey data, it's common to have missing responses that need to be handled appropriately. Similarly, when calculating average sales per month, missing data for some months should be accounted for. Handling missing values ensures accurate mean calculations and prevents biased results.
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