Fundamentals of Statistics contains material of various lectures and courses of H. Lohninger on statistics, data analysis and chemometrics......click here for more. 
Home General Processing Steps Data Preprocessing Missing Values  
See also: data matrices, exercise  
Missing Values
One major problem of any analysis of data is caused by missing values. The resulting, partially empty data matrices are hard to interpret and should be avoided whenever possible. However, several methods exist to deal with missing values.
"Proper (i.e. versatile) missing value handling is essential to any data analysis package worthy of the name" Mark Myatt, Brixton Health, UK, newsgroup sci.stat.consult, Dec 1996 Possibilities to deal with missing values:
Be sure to always mark imputed data as such.
Otherwise you may confuse it with real data later on.


Home General Processing Steps Data Preprocessing Missing Values 
Last Update: 20121008