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Modern R Programming Cookbook. Recipes to simplify your statistical applications

Język publikacji: 1
Autor:
Jaynal Abedin
Modern R Programming Cookbook. Recipes to simplify your statistical applications Jaynal Abedin - okladka książki

Modern R Programming Cookbook. Recipes to simplify your statistical applications Jaynal Abedin - okladka książki

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Stron:
236
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R is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people. There are more than 2,000 available add-ons, and R is a serious rival to all commercial statistical packages. The objective of this book is to show how to work with different programming aspects of R. The emerging R developers and data science could have very good programming knowledge but might have limited understanding about R syntax and semantics. Our book will be a platform develop practical solution out of real world problem in scalable fashion and with very good understanding. You will work with various versions of R libraries that are essential for scalable data science solutions. You will learn to work with Input / Output issues when working with relatively larger dataset. At the end of this book readers will also learn how to work with databases from within R and also what and how meta programming helps in developing applications.

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O autorze książki

Jaynal Abedin currently holds the position of Statistician at the Centre for Communicable Diseases (CCD) at icddr,b ( www.icddrb.org). He attained his Bachelor's and Master's degrees in Statistics from the University of Rajshahi, Rajshahi, Bangladesh. He has vast experience in R programming and Stata and has efficient leadership qualities. He is currently leading a team of statisticians. He has hands-on experience in developing training material and facilitating training in R programming and Stata along with statistical aspects in public health research. His primary area of interest in research includes causal inference and machine learning. He is currently involved in several ongoing public health research projects and is a co-author of several work-in-progress manuscripts. In the useR! Conference 2013, he presented a poster—edeR: Email Data Extraction using R, available at https://www.edii.uclm.es/~useR-2013/abstracts/files/34_edeR_Email_Data_Extraction_using_R.pdf—and obtained the best application poster award. He is also involved in reviewing scientific manuscripts for the Journal of Applied Statistics (JAS) and the Journal of Health Population and Nutrition (JHPN). He is also a successful freelance statistician on online platforms and has an excellent reputation through his high-quality work, especially in R programming. He can be contacted at joystatru@gmail.com, https://bd.linkedin.com/in/jaynal; his Twitter handle is @jaynal83.

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