Business statistics : a first course
著者
書誌事項
Business statistics : a first course
Pearson, c2020
8th ed., global ed
大学図書館所蔵 全2件
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  岩手
  宮城
  秋田
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  福島
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  長野
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  静岡
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  京都
  大阪
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  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
For one-semester business statistics courses.
A focus on using statistical methods to analyse and interpret results to make data-informed business decisions
Statistics is essential for all business majors, and Business Statistics: A First Course helps students see the role statistics will play in their own careers by providing examples drawn from all functional areas of business. Guided by the principles set forth by major statistical and business science associations (ASA and DSI), plus the authors' diverse experiences, the 8th Edition, Global Edition, continues to innovate and improve the way this course is taught to all students. With new examples, case scenarios, and problems, the text continues its tradition of focusing on the interpretation of results, evaluation of assumptions, and discussion of next steps that lead to data-informed decision making. The authors feel that this approach, rather than a focus on manual calculations, better serves students in their future careers. This brief offering, created to fit the needs of a one-semester course, is part of the established Berenson/Levine series.
目次
First Things First
1. Defining and Collecting Data
2. Organizing and Visualizing Variables
3. Numerical Descriptive Measures
4. Basic Probability
5. Discrete Probability Distributions
6. The Normal Distribution
7. Sampling Distributions
8. Confidence Interval Estimation
9. Fundamentals of Hypothesis Testing: One-Sample Tests
10. Two-Sample Tests
11. Analysis of Variance
12. Chi-Square and Nonparametric Tests
13. Simple Linear Regression
14. Introduction to Multiple Regression
15. Multiple Regression Model Building
16. Time-Series Forecasting
17. Business Analytics
18. Getting Ready to Analyze Data in the Future
19. Statistical Applications in Quality Management (online)
20. Decision Making (online)
Self-Test Solutions and Answers to Selected Even-Numbered Problems
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