Data Cleaning and Preprocessing
Learning techniques to identify and handle missing values, outliers, and inconsistencies in datasets to prepare for analysis.
Key Questions
- Design a strategy to handle missing data in a large dataset.
- Evaluate the impact of data outliers on statistical analysis.
- Justify the importance of data cleaning before any data analysis.
ACARA Content Descriptions
Suggested Methodologies
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