Example-driven book recommendation for learning statistics I have always found learning statistics to be hard without seeing examples, and taking for granted the answer.  I am looking for a book that teaches statistics that fits my criteria below or comes close to it:


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*teaches statistics using sample data,

*the statistical results is shown via calculations, and not my having to guess how the result was arrived,

*exercises that uses sample data along with detailed solutions, and not just an answer,

*calculations can use programming code, but not with proprietary software such as SAS, or MATLAB.


If anyone has come across such a book, that would be great.  
 A: Springer has Use R! series that introduces various statistics topics illustrated with examples in R. Among other books by this publisher there are few that are worth mentioning:


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*Introductory Statistics with R

*Modern Applied Statistics with S-Plus is a nice introduction to statistical modeling. Don't be discouraged with S-plus in the title since S is almost the same as R.

*Introductory Time Series with R

*Introducing Monte Carlo Methods with R is a great example-driven introduction to MCMC.

*An Introduction to Statistical Learning with Applications in R is generally a very good introduction to machine learning, there is also online Stanford course that accompanies the book.


All of those seem to meet your requirements - they are introductory, with multiple examples, but generally not in "use this black-box software that will compute it for you" fashion.
Of course there are better and worse books in the series, but generally you could try those as an introduction. As an additional profit you'll learn using R quite a lot from those.
