Data Scientists extract unstructured and structured data and process it through analytics into the proper format. For being a Data Scientist one needs to have proper thinking and analytical skills or else you’ll fail to become a data scientist. Data Science is a conceptual interpretation to unite statistics and analyse data with the related methods. The brainchild is to understand and employ techniques and methods that used by a data scientist to structurize the data to make it useful.
The broader fields of understanding what data science includes mathematics, statistics, computer science and information science. For those who want to make their career as a Data Scientist or in Data Analytics then you need to have a very strong background in statistics and mathematics as the big companies will always give preference to those with good analytical and statistical skills. Therefore, if one already has those skills, good but otherwise you’ll have to develop those skills and for that, you can read books that would enhance your knowledge about data science statistics.
Data Science Statistics Books are Mentioned as Follows:
1) Data Science from Scratch
Author- Joel Grus
About the Book- Joel Grus is a software engineer at Google. He has previously been a Data Scientist at startups as well. This book is for people who’ve just started to develop their skills for Data Science. So this book is going to be a great help to freshers. You’ll get a basic knowledge of Data Science and machine learning as and when you complete this book.
2) A Layperson’s Guide to Understanding Research and Data Analysis
Author- Lynda Rose Bruce Edd
About the Book- This book is made for people who have been busy and still want to dig their mind into becoming a Data Scientist. The idea behind writing this book is to make people understand what they can do with so much of information that’s been flooding them and what all they can make out of it. This book when completely read is going to give you a proper analytical and statistical skill of what you can do with the information you have.
3) Data Analytics: Essentials to Master Data Analytics and Get Your Business to the Next Level
Author- Scott Harvey
About the Book- This is an in-depth description of what and when you can make of data analytics and how can you use it in form of Data Science. This is not exactly about work of a Data Scientist but is going to help you in going about it. You’ll also get a chance to utilise the tips and techniques in business at large.
4) Data Analytics: Practical Guide to Leveraging the Power of Algorithms, Data Science, Data Mining, Statistics, Big Data, and Predictive Analysis to Improve Business, Work, and Life
Author- Arthur Zhang
About the Book- Data science is expanding in breadth and growing rapidly in importance as technology rapidly integrates ever deeper into business and our daily lives. The need for a succinct and informal guide to this important field has never been greater. Therefore, this book is going to make you engross all the vital information regarding the same.
5) Principle of Data Science
Author- Sinan Ozdemir
About the Book- This book is a must if you want to turn your programming skills effective in relation to Data Science. This going to help you in joining dots in relation to mathematics, programming and business analysis.
6) Statistical Methods for Spatial Data Analysis
Author- Carol A. Gotway
About the Book- This book is going to give you an understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses on the unique characteristics of spatial data and the development of specialised analytical tools designed explicitly for spatial data analysis. Statistical Methods for Spatial Data Analysis answers the demand for a text that incorporates all of these factors by presenting a balanced exposition that explores both the theoretical foundations of the field of spatial statistics as well as practical methods for the analysis of spatial data.
7) Statistics: A Very Short Edition
Author- David J. Hand
About the Book- Statistical ideas and methods underlie just about every aspect of modern life. From randomised clinical trials in medical research to statistical models of risk in banking and hedge fund industries to the statistical tools used to probe vast astronomical databases, the field of statistics has become centrally important to how we understand our world. But the discipline underlying all these is not the dull statistics of the popular imagination. Long gone are the days of manual arithmetic manipulation.
Must Read- Data Science Statistics Blogs
1) Blog About Stats
This blog by Armin Grossenbacher is going to help you with all the professional help that you need while disseminating the official statistics. To know more, go to his blog (https://blogstats.wordpress.com/).
The author of this blog is Ajay Ohri and he is very active on the blog which makes it altogether more effective in learning for the reader as he is always updated with the new things. Go and find more about his (blog https://decisionstats.com/).
3) Error Statistics Philosophy
This blog is regulated by Virginia Tech statistical philosopher Deborah G. Mayo and is going to be very useful in your professional life. Find more on (https://errorstatistics.com/).
4) R Statistics
This blog by Tal Galili, a PhD student in Statistics at the Tel Aviv University and also works as an assistant for teaching statistics courses in the university. This blog is going to help you with the language R and the statistical knowledge related to it. ( https://www.r-statistics.com/)
Is Statistics Needed for Data Science
Statistics has a very wide horizon and that is how one can applicate it in data science statistics. Statistics is the study of the collection, organisation analysis, interpretation and organisation of data. Therefore, data scientists need to know statistics. Data Analysis requires descriptive statistics and probability theory that can help one in making better business decisions.