The practice of business statistics : using data for decisions
著者
書誌事項
The practice of business statistics : using data for decisions
W.H. Freeman, c2003
Comprehensive version
- : CD-ROM
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注記
"Includes all 18 chapters" -- Cover
Includes indexes
内容説明・目次
内容説明
This text and CD-ROM immerses students in the course immediately, involving them in practical, statistics-supported business decision making from the outset. Using real data to provide a context for tackling modern business problems, the book introduces a range of core ideas early including data production and interpretation. The usefulness of statistical concepts in contemporary business, the connections between probability and inference, and the relationship between data and decisions are emphasised. From this beginning, the text continually revisits and builds on what students have learned, re-purposing data sets from previous examples and exercises to explore different decision models in different situations. Pedagogically, the title brings a number of new learning tools to the business statistics textbook, including: case studies - introduced in every chapter, the cases dramatise key concepts.
Selected examples in the chapter refer back to the cases, and chapter ending pedagogy includes case study exercises; applet exercises - in some exercises (indicated with an icon), students work with manipuable data via applets on the Web site and/or CD; and applications - students see the immediate relevance of what they're learning through coverage of: consumer's supermarket shopping habits; returns on common stocks; salary distributions; stocks and bonds; forecasting earnings; and mutual fund performance.
目次
Examining Distributions - Examining Relationships - Producing Data - Probability and Sampling Distributions - Probability Theory - Introduction to Inference - Inference for Distributions - Inference for Proportions - Inference for Two-Way Tables - Inference for Regression - Multiple Regression - Statistical Quality: Control and Capability - Time Series Forecasting - One-Way Analysis of Variance - Two-Way Analysis of Variance - Nonparametric Tests - Logistic Regression - Bootstrap Methods and Permutation Tests
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