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It seems like most statistics books over-complicate the examples of most concepts.

For example, I encountered recently a text that illustrates singular values decomposition with visual recognition, instead of the simpler idea of finding the best way to rotate an ellipse to calculate the lengths of its axes.

This confuses not only the less experienced mathematicians, but even those who have a good understanding of the underlying concepts, which are often elementary.

Is there a text that explains statistical concepts with toy examples, instead of dazzling one with huge numbers and large amount of data?

EDIT: As pointed out in the commentaries, I must specify that I am looking for a book that is more on the applied side, more geared towards machine learning/hypothesis testing, yet with toy examples. I want it to be comprehensive, covering all of the major topics. I a am a fan of Introduction to Statistical Learning so far, but the examples in it are not to my liking, as they seem overly complicated.

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  • $\begingroup$ Introductory, intermediate or advanced? Theoretical or applied? And remember one man's meal is another's poison $\endgroup$ – Sam May 20 '20 at 15:46
  • $\begingroup$ @Sam Please see the edit. $\endgroup$ – user22835 May 20 '20 at 17:04
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    $\begingroup$ Does this answer your question? Recommend a statistics fundamentals book $\endgroup$ – Intellectually disabled Dec 26 '20 at 21:16