Statistics looks so difficult, no way to simplify ?

[lalbatros]

Beyond the basics (mean, variance, distributions, simple test, regression, ...) statistics looks like a huge mess -to me- .

Any method has typically 10 variants and can be 'colored' in 10 flavors,
not to mention technicalities like missing data handling, binary data, ... and people's names
I need to think a long time before I understand the main point of a method (say the bartlett test in a PCA).
I never feel confident for "the details and the options".
Many things never get translated in simple words.
Mathematical descriptions are not (easily) available or are (practically) unreadable.

Sometimes I have the feeling that a "huge monte carlo" point of view could help to simplify the understanding.
For example, a statistical test could be implemented by a "monte carlo" method. If computers had a huge computing power, recourse to specific tests (hard to develop, get and understand) would be useless.
At least, this could be a language to express a "statistical problem".

Could some of you give me some related ideas, papers or web sites?
I am equally interrested by nicely-written material, organized references, unification attempts.
I would like to see the forest, not the trees.

 

[EnumaElish]

http://en.wikipedia.org/wiki/Monte_Carlo_method#References

 

[tacman]

It is understandable that statistics can seem overwhelming and complex, especially when delving into more advanced topics beyond the basics. However, it is important to keep in mind that statistics is a broad and diverse field, with various methods and techniques available for different purposes. It is not necessary to understand every single method in order to have a solid understanding of statistics. Instead, it is important to focus on the methods and techniques that are most relevant to your specific needs and goals.

One way to simplify statistics is to break it down into smaller, more manageable parts. For example, rather than trying to understand all 10 variants and 10 flavors of a particular method, focus on the core principles and how they can be applied in different scenarios. It can also be helpful to think about statistics as a problem-solving tool, rather than a collection of complex formulas and techniques. By understanding the underlying concepts and principles, it becomes easier to apply them in different situations and adapt to new challenges.

In terms of resources, there are many helpful books, websites, and online courses available that can provide a more structured and organized approach to learning statistics. It may also be helpful to seek out a mentor or join a study group where you can discuss and work through challenging topics together. Additionally, many statistical software programs have built-in help and tutorials that can guide you through the different options and features.

Finally, it is important to remember that it takes time and practice to become comfortable with statistics. Just like any other skill, it requires patience, persistence, and a willingness to continue learning and improving. Don't get discouraged if you don't understand everything right away, and don't be afraid to ask for help when needed. With dedication and effort, you can develop a solid understanding of statistics and feel more confident in your abilities.