Aimed at upper-division undergraduates majoring in statistics, as well as graduate students from a variety of disciplines (business, psychology, education, and sociology) who need to use sophisticated statistical methods in their research and other professional activities. This is a comprehensive textbook for a course in statistical methods, primarily aimed at majors other than statistics in upper-division undergraduate- and graduate level courses. The use of this book in a two-semester course sequence provides a complete overview of most standard statistical methods, including a substantial amount of material on multiple regression, analysis of variance, experimental design, and sampling techniques. In addition, the text is organized in a manner to provide a useful subset of methods is used for only one semester. The primary purpose throughout is to teach intelligent data analysis and principles of good data collection, including the intelligent use of computers to assist in drawing conclusions about data. The only mathematical background necessary is two years of school algebra. Features include a comprehensive overview of most standard statistical methods - multiple regression, analysis of variance, experimental design, and sampling techniques; a useful subset of methods if used for only one semester; learning concepts as opposed to the "plugging numbers into formulas" approach.
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Aimed at upper-division undergraduates majoring in statistics, as well as graduate students from a variety of disciplines (business, psychology, education, and sociology) who need to use sophisticated statistical methods in their research and other professional activities. This is a comprehensive textbook for a course in statistical methods, primarily aimed at majors other than statistics in upper-division undergraduate- and graduate level courses. The use of this book in a two-semester course sequence provides a complete overview of most standard statistical methods, including a substantial amount of material on multiple regression, analysis of variance, experimental design, and sampling techniques. In addition, the text is organized in a manner to provide a useful subset of methods is used for only one semester. The primary purpose throughout is to teach intelligent data analysis and principles of good data collection, including the intelligent use of computers to assist in drawing conclusions about data. The only mathematical background necessary is two years of school algebra. Features include a comprehensive overview of most standard statistical methods - multiple regression, analysis of variance, experimental design, and sampling techniques; a useful subset of methods if used for only one semester; learning concepts as opposed to the "plugging numbers into formulas" approach.
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