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＜電子ブック＞
Statistics in Scientific Investigation : Its Basis, Application, and Interpretation / by Glen McPherson
(Springer Texts in Statistics. ISSN:21974136)

版	1st ed. 1990.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	1990
本文言語	英語
大きさ	XXVI, 667 p : online resource
著者標目	*McPherson, Glen author SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Biometry FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Biostatistics
一般注記	1 The Role of Statistics in Scientific Investigation -- 2 Data: The Factual Information -- 3 Statistical Models: The Experimenter’s View -- 4 Comparing Model and Data -- 5 Probability: A Fundamental Tool of Statistics -- 6 Some Widely Used Statistical Models -- 7 Some Important Statistics and Their Sampling Distributions -- 8 Statistical Analysis: The Statisticians’ View -- 9 Examining Proportions and Success Rates -- 10 Model and Data Checking -- 11 Questions About the “Average” Value -- 12 Comparing Two Groups, Treatments or Processes -- 13 Observational Studies, Surveys and Designed Experiments -- 14 Comparing More Than Two Treatments or Groups -- 15 Comparing Mean Response When There Are Three or More Treatments -- 16 Comparing Patterns of Response: Frequency Tables -- 17 Studying Association and Correlation -- 18 Prediction and Estimation: The Role of Explanatory Variables -- 19 Questions About Variability -- 20 Cause and Effect: Statistical Perspectives -- 21 Studying Change in Response over Time -- 22 Computers and Statistics -- Appendix A: Tables for Some Common Probability Distributions -- References -- Figure, Table, and Example Index In this book I have taken on the challenge of providing an insight into Statistics and a blueprint for statistical application for a wide audience. For students in the sciences and related professional areas and for researchers who may need to apply Statistics in the course of scientific experimenta­ tion, the development emphasizes the manner in which Statistics fits into the framework of the scientific method. Mathematics students will find a unified, but non-mathematical structure for Statistics which can provide the motivation for the theoretical development found in standard texts on theoretical Statistics. For statisticians and students of Statistics, the ideas contained in the book and their manner of development may aid in the de­ velopment of better communications between scientists and statisticians. The demands made of readers are twofold: a minimal mathematical prerequisite which is simply an ability to comprehend formulae containing mathematical variables, such as those derived from a high school course in algebra or the equivalent; a grasp of the process of scientific modeling which comes with ei­ ther experience in scientific experimentation or practice with solving mathematical problems HTTP:URL=https://doi.org/10.1007/978-1-4757-4290-9

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