Title
An Introduction To Statistics With Python: With Applications In The Life Sciences (Statistics And Computing)
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Reviewthis 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 Handson 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. (Irina Ioana Mohorianu, Zbmath 1357.92001, 2017)Product Descriptionthis Textbook 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 Easytofollow 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 Is Intended For 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.From The Back Coverthis Textbook 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 Easytofollow 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 Is Intended For 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.About The Authorthomas Haslwanter Is A Professor At The Department Of Medical Engineering Of The University Of Applied Sciences Upper Austria In Linz, And Lecturer At The Eth Zurich In Switzerland. He Also Worked As A Researcher At The University Of Sydney, Australia And The University Of Tuebingen, Germany. He Has Extensive Experience In Medical Research, With A Focus On The Diagnosis And Treatment Of Vertigo And Dizziness And On Rehabilitation. After 15 Years Of Extensive Use Of Matlab, He Discovered Python, Which He Now Uses For Statistical Data Analysis, Sound And Image Processing, And For Biological Simulation Applications. He Has Been Teaching In An Academic Environment For More Than 10 Years.
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- Q: How many pages does this book have? A: This book has two hundred ninety-five pages. It covers a wide range of statistical concepts and applications.
- Q: What are the dimensions of this textbook? A: The textbook measures six point five inches in length, zero point seventy-five inches in width, and nine point five inches in height. These dimensions make it a standard hardcover size.
- Q: What type of binding does this book have? A: This book has a hardcover binding. This type of binding provides durability and longevity for frequent readers.
- Q: What is the main focus of this book? A: The main focus is on using Python for statistical data analysis. It is designed for master and PhD students in the life and medical sciences.
- Q: Who is the author of this book? A: The author of this book is Thomas Haslwanter. He has expertise in both statistics and Python programming.
- Q: What topics are covered in this textbook? A: The textbook covers statistical tests, linear regression, survival analysis, and Bayesian statistics. It provides practical coding examples for each topic.
- Q: How do I apply the concepts learned in this book? A: You can apply the concepts by reproducing the examples and working through the provided Python code. This hands-on approach reinforces learning.
- Q: Is this book suitable for beginners in statistics? A: Yes, this book is suitable for beginners with a basic knowledge of statistics. It offers foundational concepts alongside practical applications.
- Q: Can I use this book for self-study? A: Yes, this book is ideal for self-study. It includes clear examples and exercises for independent learning.
- Q: Is there any prerequisite knowledge needed to read this book? A: A basic knowledge of statistics is recommended to fully benefit from this book. It helps in understanding advanced topics more easily.
- Q: How should I store this textbook to keep it in good condition? A: Store this textbook in a cool, dry place, standing upright or flat. Avoid direct sunlight to prevent fading of the cover.
- Q: How do I clean the book if it gets dirty? A: To clean the book, gently wipe the cover with a soft, dry cloth. Avoid using any liquids that could damage the paper.
- Q: What if I receive a damaged copy of this book? A: If you receive a damaged copy, contact the seller for a return or exchange. Most sellers have policies in place for such issues.
- Q: Is this book available in digital format? A: Yes, this textbook may be available in digital format. Check with the publisher or retailer for eBook options.
- Q: Does the book include exercises or practice problems? A: Yes, the book includes exercises and practice problems. These are designed to reinforce the concepts learned in each chapter.
- Q: What makes this book different from others on statistics? A: This book focuses specifically on Python for statistical analysis, providing practical coding examples. It is tailored for students in the life sciences.