| 书目名称 | Learning Regression Analysis by Simulation | | 编辑 | Kunio Takezawa | | 视频video | | | 图书封面 |  | | 描述 | .The standard approach of most introductory books for practical statistics is that readers first learn the minimum mathematical basics of statistics and rudimentary concepts of statistical methodology. They then are given examples of analyses of data obtained from natural and social phenomena so that they can grasp practical definitions of statistical methods. Finally they go on to acquaint themselves with statistical software for the PC and analyze similar data to expand and deepen their understanding of statistical methods..This book, however, takes a slightly different approach, using simulation data instead of actual data to illustrate the functions of statistical methods. Also, R programs listed in the book help readers realize clearly how these methods work to bring intrinsic values of data to the surface. R is free software enabling users to handle vectors, matrices, data frames, and so on..For example, when a statistical theory indicates that an event happens with a 5 % probability, readers can confirm the fact using R programs that this event actually occurs with roughly that probability, by handling data generated by pseudo-random numbers. Simulation gives readers populat | | 出版日期 | Book 2014 | | 关键词 | Akaike‘s Information Criterion (AIC); basic concepts of linear algebra; basic concepts of statistics; l | | 版次 | 1 | | doi | https://doi.org/10.1007/978-4-431-54321-3 | | isbn_softcover | 978-4-431-56143-9 | | isbn_ebook | 978-4-431-54321-3 | | copyright | Springer Japan 2014 |
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发表于 2025-3-21 16:34:02
