Data Mining vs Data Snooping

Data Snooping

In the article “data mining vs data snooping”, we will discuss what is data snooping. Data Snooping is a statistical mistake that occurs when a researcher looks at the data before having its statistical guidelines. Data Snooping occurs when a given set of data is used more than once for purposes of inference selection, and these are called the problems of multiple inference.

Data Snooping is done on small data sets without any specific goal, and this is often done by hand (manually), which can lead to fake conclusions.

Pros of Data Snooping

• Data snooping provides rapid insights into datasets without the need for a predefined research hypothesis
   
• Data snooping can lead to some unexpected findings that might have not been discovered by the traditional hypothetical approaches
   
• New research ideas can be generated by analyzing the data with data snooping
   
• Data snooping also helps the organizations to make data-driven decisions

Cons of Data Snooping

• The choices of researchers in the analysis methods can introduce bias which may impact the result
   
• There is a risk of drawing incorrect conclusions with the data snooping
   
• Models can perform well on the existing data but may fail in new or unseen data

Difference between Data Mining and Data Snooping

In the article “data mining vs data snooping”, now we will discuss the important part, the difference between data mining and data snooping:

Frequently Asked Questions

What is Data Mining?

Data Mining consists of some techniques and tools which are used by scientists to find out the properties of datasets and produce insightful information which can be used by organizations.

What are the types of data mining?

Here are the following types of data on which data mining can be performed are Relational Databases, Data Warehouses, Object-Relational Databases, and Transactional databases, etc.

What is Data Snooping?

Data Snooping is a statistical mistake that occurs when a researcher looks at the data before having its statistical guidelines, which is done on small data sets and can lead to false conclusions.

What are the pros of data snooping?

It provides rapid insights into datasets without the need for a predefined research hypothesis. It can lead to some unexpected findings that might have not been discovered by the traditional hypothetical approaches. New research ideas can be generated by analysing the data with data snooping.

What are the pros of data mining?

Data mining helps in the decision-making in an organisation and to obtain knowledge-based data. The process of data mining is cost-effective and is very quick which makes it easy for the users to analyse the amount of data in a short period of time.

Conclusion

Both Data Mining and Deep Learning are areas inspired by each other, yet they have different ends. Data mining is used for producing insightful information that can be used by the organization for identifying sales patterns or trends. On the other hand, Data Snooping is a statistical mistake that occurs when a researcher looks at the data before having its statistical guidelines.

In the article “data mining vs data snooping”, we discussed what is data mining along with its types, pros, and cons, what is data snooping with its types, pros, and cons, and the difference between data mining and data snooping.

Here are more articles that are recommended to read:

• What is Data Science?
• Introduction to Artificial Intelligence
• Complete Introduction to Data Mining
• Applications of Data Mining

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