Applied Statistics: Theory and Problem Solutions with R
Authors: Dieter Rasch – Rob Verdooren – Jürgen Pilz
ISBN-10: 1119551528
ISBN-13: 9781119551522
Edition 版次: 1
Publication Date 出版日期: 2019-10-07
Print Length 页数: 472 pages
Book Description
By finelybook
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
Preface
1The R-Package,Sampling Procedures,and Random Variables
2 Point Estimation
3Testing Hypotheses-One-and Two-Sample Problems
4Confidence Estimations-One-and Two-Sample Problems
5Analysis of Variance(ANOVA)-Fixed Effects Models
6Analysis of Variance-Models with Random Effects
7 Analysis of Variance-Mixed Models
8 Regression Analysis
9 Analysis of Covariance (ANCOVA)
10 Multiple Decision Problems
11 Generalised Linear Models
12Spatial Statistics
Appendix A: List of Problems
Appendix B: Symbolism
Appendix C: Abbreviations
Appendix D. Probability and Density Functions
Index
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