What is a common method for handling missing data in a dataset?

Practice Questions

Q1
What is a common method for handling missing data in a dataset?
  1. Removing all rows with missing values
  2. Imputing missing values with the mean or median
  3. Ignoring the missing values
  4. All of the above

Questions & Step-by-Step Solutions

What is a common method for handling missing data in a dataset?
  • Step 1: Identify the missing data in your dataset.
  • Step 2: Determine the amount of missing data (e.g., is it a small percentage or a large percentage?).
  • Step 3: Choose a method to handle the missing data. Common methods include: removing rows with missing data, filling in missing values with the mean or median, or using algorithms that can handle missing data.
  • Step 4: Apply the chosen method to your dataset.
  • Step 5: Review the dataset after handling the missing data to ensure it meets your analysis needs.
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