Intermediate Statistical Methods

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Intermediate Statistics

Author: James P. Stevens
language: en
Publisher: Lawrence Erlbaum Associates
Release Date: 1999-09-01
James Stevens' best-selling text, Intermediate Statistics is written for those who use, rather than develop, statistical techniques. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving the results. SAS and SPSS are an integral part of each chapter. Definitional formulas are used on small data sets to provide conceptual insight into what is being measured. The assumptions underlying each analysis are emphasized and the reader is shown how to test the critical assumptions using SPSS or SAS. Printouts with annotations from SAS or SPSS show how to process the data for each analysis. The annotations highlight what the numbers mean and how to interpret the results. Numerical, conceptual, and computer exercises enhance understanding. Answers are provided for half of the exercises.
Statistical Analysis and Data Display

Author: Richard M. Heiberger
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-06-29
1 Audience Students seeking master's degrees in applied statistics in the late 1960s and 1970s typically took a year-long sequence in statistical methods. Popular choices of the course text book in that period prior to the availability of high speed computing and graphics capability were those authored by Snedecor and Cochran, and Steel and Torrie. By 1980, the topical coverage in these classics failed to include a great many new and important elementary techniques in the data analyst's toolkit. In order to teach the statistical methods sequence with adequate coverage of topics, it became necessary to draw material from each of four or five text sources. Obviously, such a situation makes life difficult for both students and instructors. In addition, statistics students need to become proficient with at least one high-quality statistical software package. This book can serve as a standalone text for a contemporary year-long course in statistical methods at a level appropriate for statistics majors at the master's level or other quantitatively oriented disciplines at the doctoral level. The topics include both concepts and techniques developed many years ago and a variety of newer tools not commonly found in textbooks.