Data cleaning

Tips/Tricks for Data cleaning...

(this page has just been created... can you think of more tips to add...)

Always first look at distributions of data and outlier analysis.
Try to be consistent in what outliers method you use when cleaning data.
S+ and other robust procedures inherently correct for outliers.
SPSS tukey’s box plot rule and graph’s boxlot allow you to see outliers
Winzoring is another good idea.
Both univariate and Multivariate outlier analysis should be conducted.
For pure data cleaning, such as out of range or missing data, maybe you should spot check R.A data entry to make sure data is being entered correctly
Try having variable data file that codes for who entered which parts of the data.
Try to enter the data at least twice because everyone makes mistakes, even you.