# Applied Statistics: Theory and Problem Solutions with R

93,30€

ISBN: 9781119551546
DRM Restrictions

Printing 154 pages with an additional page accrued every 5 hours, capped at 154 pages 5 excerpts

Instructs readers on how to use methods of statistics and experimental design with R software

Applied statistics covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce, and research. It proceeds from a strong theoretical background, but it is practically oriented to develop one's ability to tackle new and non-standard problems confidently. Taking a practical approach to applied statistics, this user-friendly guide teaches readers how to use methods of statistics and experimental design without going deep into the theory.

Applied Statistics: Theory and Problem Solutions with R includes chapters that cover R package sampling procedures, analysis of variance, point estimation, and more. It follows on the heels of Rasch and Schott's Mathematical Statistics via that book's theoretical background—taking the lessons learned from there to another level with this book’s addition of instructions on how to employ the methods using R. But there are two important chapters not mentioned in the theoretical back ground as Generalised Linear Models and Spatial Statistics.

• Offers a practical over theoretical approach to the subject of applied statistics
• Provides a pre-experimental as well as post-experimental approach to applied statistics
• Features classroom tested material
• Applicable to a wide range of people working in experimental design and all empirical sciences
• Includes 300 different procedures with R and examples with R-programs for the analysis and for determining minimal experimental sizes

Applied Statistics: Theory and Problem Solutions with R will appeal to experimenters, statisticians, mathematicians, and all scientists using statistical procedures in the natural sciences, medicine, and psychology amongst others.

Keywords:

applied statistics; statistical theory; data analysis; data science; probability; statistics; R software; optimization; experimental design; design of experiments; applied statistics; analysis; R package; variance analysis; point estimation; multiple decision problems; selection procedures; spatial statistics

, Statistical Software / R, Experimental Design, Statistical Software / R, Experimental Design
Author(s)

Publisher
John Wiley and Sons, Inc.
Publication year
2020
Language
en
Edition
1
Page amount
512 pages
Category
Natural Sciences
Format
Ebook
eISBN (ePUB)
9781119551546
Printed ISBN
9781119551522