µ Read ¶ An Introduction to Statistics With Python : With Applications in the Life Sciences by Thomas Haslwanter Ô royalfm.pro
µ Read ¶ An Introduction to Statistics With Python : With Applications in the Life Sciences by Thomas Haslwanter Ô This Text Book Provides An Introduction To The Free Software Python And Its Use For Statistical Data Analysis It Covers Common Statistical Tests For Continuous, Discrete And Categorical Data, As Well As Linear Regression Analysis And Topics From Survival Analysis And Bayesian Statistics Working Code And Data For Python Solutions For Each Test, Together With Easy To Follow Python Examples, Can Be Reproduced By The Reader And Reinforce Their Immediate Understanding Of The Topic With Recent Advances In The Python Ecosystem, Python Has Become A Popular Language For Scientific Computing, Offering A Powerful Environment For Statistical Data Analysis And An Interesting Alternative To R The Book Addresses The Needs Of Master And PhD Students, Mainly From The Life And Medical Sciences, With A Basic Knowledge Of Statistics As It Also Provides Some Statistics Background, The Book Can Be Used By Anyone Who Wants To Perform A Statistical Data Analysis 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 and 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 than half the mean I stopped reading, there is probably of this nonsense Do not read the part on statistics, you will only learn fables The statistics part would make an undergrad students f
Good content, but the Kindle version is nothing than a PDF file Very disappointed 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.