8 COMMON MISTAKES MADE IN DATA SCIENCE/STATISTICAL MODELLING

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Here I discuss about some of the common mistake made by people in data science modelling.
1- not defining the problem statement well
2- Sample is not representative
3- Misuse of p-value
4-Lack of proper data quality checks
5- Improper model validation/cross validation
6- Not checking if model assumptions are valid
7- Not having a proper monitoring strategy

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