Hamed Kioumarsi says: My colleagues and I finished the book this year. The book will be available internationally in print and digital formats. Writing a book is time-consuming and expensive, but the rewards, if you are persistent, can be immense.
Dr. Alidoust and Dr. Kioumarsi are senior researchers working at Gilan Agricultural and Natural Resources Research Center, and Dr. Allen is a research scientist with invaluable cross-cultural experience and understanding, who has conducted agricultural research at Universiti Sains Malaysia, the University of the Philippines at Los Baños, the University of Florida, and New Mexico State University, among others.
The World we are living in is descending into Chaos, and it is verified by physics! Physicists believe the Earth System gets into the region of chaotic behavior and maybe learning data science is a way to predict and track the changes in our surrounding environment and to learn how to survive and to live with it.
Data scientists are likely to face a growing demand for their skills in different fields. We were researching the highest-paying jobs that are predicted to be in demand for the future and interestingly, the data scientists are at the top of the list. A decade ago, technologists Thomas H. Davenport and D.J. Patil declared data scientists the most attractive job of the future. And their prediction has become true as the world becomes increasingly reliant on digital information.
Notably, data science is in some ways the future of everything, so increasingly decisions can be made utilizing it. In this book, we try to give a brief overview of data science, and try to make it a practical guide. Properly used statistical principles are essential in guiding any inquiry informed by data. Statistics is a mathematical science that is concerned with the collection, analysis, and interpretation of data. There is no doubt that with the rapid changes in science and technology, statistical thinking will one day be as necessary a qualification for efficient citizenship as the ability to read and write (Watkins, 2016).
Different chapters make a contribution to theoretical and methodological foundations of information technological know-how, along with qualitative vs. Quantitative studies, facts collection, MS Excel, SPSS, Python, synthetic intelligence and system studying, and statistics technology in agriculture.
The book is a good source for those who plan to build a career in data science, such as becoming a data scientist. Faculty and Staff will be using this book to educate students and graduates of universities in Iran. The book is written for use in Iran, and we trust that the content may be helpful for learners in Iran as well as those in other contexts who may wish to learn about data science in a practical way.
The e-book is authored by way of Dr. Hamed Kioumarsi (Gilan Agricultural and Natural Resources Research and Education Center, AREEO, Iran), Dr. Marzieh Alidoust (Gilan Agricultural and Natural Resources Research and Education Center, AREEO, Iran), and Dr. Samuel C. Allen (SAE Services, Farmington, New Mexico, USA).
