One of the most common problems we face in Data Cleaning/Exploratory Analysis is handling the missing values. Firstly, understand that there is NO good way to deal with missing data. We have come across different solutions for data imputation depending on the kind of problem Time series analysis, Regression etc. and it is difficult to provide a general solution.

Question to consider:

How do you suggest students in Research Methods should handle missing data as a result of your survey and/or focus group session?