Stop! Avoid These 10 Common Data Analysis Errors

Many People often makes these 10 mistakes while analyzing their data. Don’t be one of them, Avoid them now !

Photo by Myriam Jessier on Unsplash

1. Ignoring Data Cleaning

• Mistake: Analyzing messy and raw data.
• Solution: Always do clean your data by handling missing values, duplicates, and inconsistencies.

2. Lack of Data Validation

• Mistake: Trusting data without verifying its accuracy or source is a big mistake.
• Solution: Validate your data by checking for errors, inconsistencies, and reliable sources before proceeding.

3. Overlooking Outliers

• Mistake: Ignoring or removing outliers without analysis.
• Solution: Investigate outliers to determine if they are errors or valuable insights.

4. Misinterpreting Correlation and Causation

• Mistake: Assuming correlation means causation.
• Solution: Use statistical tests to determine causal relationships.

5. Using the Wrong Visualization

• Mistake: Choosing inappropriate charts or graphs.
• Solution: Match the…