How do I choose the right statistical method for machine learning?

What factors should I consider when choosing a statistical method for my machine learning project?

You should consider the type of data you have, the problem you're trying to solve, and the assumptions of each method.

Can you give me examples of different statistical methods and when to use them?

Sure! For regression tasks, you might use linear regression or logistic regression. For classification, consider decision trees or support vector machines.

How do I know if a method is suitable for my data?

You can check the assumptions of the method against your data characteristics, such as distribution and sample size.

What if my data doesn't meet the assumptions of a method?

In that case, you might need to transform your data, choose a different method, or use techniques like bootstrapping.