How do you handle missing values in a dataset without introducing bias?

In Data analytics training, handling missing values involves techniques like imputation using mean, median, or mode, predictive modeling, or removing incomplete records when appropriate. The goal is to preserve data integrity while minimizing bias, ensuring that analysis results remain accurate, reliable, and reflective of real-world trends.
-
Salary Trends for Data Analysts in the USA
16 hours ago
-
How can Excel still be relevant in the age of Power BI and Tableau?
2 days ago
-
Data Visualization Tips Every Analyst Should Know
4 days ago
-
How Important Is SQL in Data Analytics?
5 days ago
-
What Are the Key Stages of the Data Analytics Lifecycle?
6 days ago
Latest Post: What tools are used in AI and Machine Learning courses? Our newest member: rafaelakutch Recent Posts Unread Posts Tags
Forum Icons: Forum contains no unread posts Forum contains unread posts
Topic Icons: Not Replied Replied Active Hot Sticky Unapproved Solved Private Closed