文档介绍：To Isa
Preface
Taken literally, the title “All of Statistics” is an exaggeration. But in spirit,
the title is apt, as the book does cover a much broader range of topics than a
typical introductory book on mathematical statistics.
This book is for people who want to learn probability and statistics quickly.
It is suitable for graduate or advanced undergraduate students puter
science, mathematics, statistics, and related disciplines. The book includes
modern topics like nonparametric curve estimation, bootstrapping, and clas-
sification, topics that are usually relegated to follow-up courses. The reader is
presumed to know calculus and a little linear algebra. No previous knowledge
of probability and statistics is required.
Statistics, data mining,andmachine learning are all concerned with
collecting and analyzing data. For some time, statistics research was con-
ducted in statistics departments while data mining and machine learning re-
search was conducted puter science departments. Statisticians thought
puter scientists were reinventing the wheel. Computer scientists
thought that statistical theory didn’t apply to their problems.
Things are changing. Statisticians now recognize puter scientists
are making novel contributions puter scientists now recognize the
generality of statistical theory and methodology. Clever data mining algo-
rithms are more scalable than statisticians ever thought possible. Formal sta-
tistical theory is more pervasive puter scientists had realized.
Students who analyze data, or who aspire to develop new methods for
analyzing data, should be well grounded in basic probability and mathematical
statistics. Using fancy tools like s, boosting, and support vector
viii Preface
machines without understanding basic statistics is like doing brain surgery
before knowing how to use a band-aid.
But where can students learn basic probability and statistics quickly? Nowhere.
At least, that was my conclusion when puter sc