An Introduction to Statistics with Python: With Applications in the Life Sciences (Statistics and Computing)

After reading the book, I realized that the author does not even understand the basics of statistics. I wonder why the author has even decided to write a book in this subject! One reason can be that since the author's language is German, the non-technical English translator has turned it into bunch of non-sense! Just to clarify, I only bought the book to see if I can refer it to my students who are interested in using Python for statistical analysis.

Good content, but the "Kindle" version is nothing more than a PDF file. Very disappointed!

There are several conceptual flaws in the writing, e.g. "Since the likelihood of finding any given value cannot be less than zero, and since the variable has to have some value, the PDF p(x) has the following properties.." I teach statistics to engineers. You will not pass my class if this is understanding of "likelihood" and "PDF".

Dr Haslwanter was kind enough to provide me with an early copy of his book, which I found to be immensely helpful. The book provides a great overview of Python tools for hypothesis testing, probability distributions, common statistical tests, and statistical modeling. It even includes a chapter on Bayesian analysis! The book provide elegant code that applies the statistical methods to scenarios in the biological sciences which I found especially helpful. It is a very thoughtful and well written book, and fills a needed gap in the scientific python literature.

I have been teaching probability and statistics for many years and I started reading this ebook to learn Python. It did help with Python, but I couldn’t believe what I was reading when I got to the ‘statistics’ part. Section 5.2.2: “a random variate x is a particular outcome of a random variable X”, Sect. 5.2.3: “The PDF also defines the expected value E[X] of a continuous distribution of X”; “If the experiment has been designed correctly, the sample mean should converge to the expected value as more and more samples are included in theanalysis”; Sect. 6.1.3: for measurements that cannot be negative, which is usually the case, we can infer that the data have a skewed distribution if the standard deviation is more than half the mean”. I stopped reading, there is probably more of this nonsense. Do not read the part on statistics, you will only learn fables. The statistics part would make an undergrad students fail. Springer had a high reputation a few decades ago, now they really are publishing rubbish.

"This book is a timely addition designed to bridge the gap between statisticians/computer scientists and experimentalists (biologists, physicists, medical doctors) by focussing on solutions to practical problems … . the book also provides hands-on examples and exercises for a better understanding (for which the solutions are included at the end of the book). This approach makes the book appealing to a wide audience ranging from undergraduates in various subjects to established researchers looking for a focused set of answers."

A superb introduction to statistics using Python, replete with coded examples and access to online resource code. An excellent introductory text which also teaches early-stage statistics and introductory Python.

Usually such books cover data science topics, but I love how the authors cover health science topics touching statistics, while demonstrating the application of these concepts using Python. I only wish the book had also touched upon epidemiology and spread of infectious disease along with Bioinformatics. But truth be told, those two topics deserve to be covered separately in their own right.

I bought this book with the idea to learn how to apply statistic knowledge with python. I got dissapointed and have to say that this book is not worth to read it. Some examples:- definitions are verbally statet but not defined by using a formular or at least using a python statement for its calculation (e.g. Chapter 6.1.3. Skeweness)- For explaining the meaning of a term one is referred to a figure- statistical values are introduced and for some a python statement is given and for some there is no statement.- Some formulars are wrong or misleading (e.g. definition of expected value, formular (5.4))This is only a short summary of the horrible presentation. Save your money and invest it in books you can trust the content and you really can learn something.

Excellent book, with running examples in Phyton