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Working with sample data : exploration and inference / Priscilla Chaffe-Stengel, Donald N. Stengel.

By: Contributor(s): Material type: TextTextPublisher number: 2 | BEPSeries: Quantitative approaches to decision making collectionPublisher: [New York, N.Y.] (222 East 46th Street, New York, NY 10017) : Business Expert Press, [(c)2011.]Edition: 1st edDescription: 1 electronic text (x, 151 pages) : illustrations, digital fileContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781606492147
Subject(s): Genre/Form: Additional physical formats: Print version:: No titleLOC classification:
  • HF1017
Online resources: Available additional physical forms:
Contents:
About the authors -- Chapter 1. Depicting data in telling ways -- Chapter 2. Summarizing location, scatter, and relative position -- Chapter 3. Understanding the normal distribution and the t- distribution -- Chapter 4. Using proof by contradiction to draw conclusions -- Chapter 5. Testing two population means and proportions -- Chapter 6. Analysis of variance from two or more populations -- Chapter 7. Testing proportions from two or more populations -- Chapter 8. Analyzing bivariate data -- Appendix. z-table, t-table, F table, and Chi-square table -- Index.
Abstract: Managers and analysts routinely collect and examine key performance measures to better understand their operations and make good decisions. Being able to render the complexity of operations data into a coherent account of significant events requires an understanding of how to work well with raw data and to make appropriate inferences. Although some statistical techniques for analyzing data and making inferences are sophisticated and require specialized expertise, there are methods that are understandable and applicable by anyone with basic algebra skills and the support of a spreadsheet package. By applying these fundamental methods themselves rather than turning over both the data and the responsibility for analysis and interpretation to an expert, managers will develop a richer understanding and potentially gain better control over their environment. This text is intended to describe these fundamental statistical techniques to managers, data analysts, and students. Statistical analysis of sample data is enhanced by the use of computers. Spreadsheet software is well suited for the methods discussed in this text. Examples in the text detail for the reader how to apply Microsoft Excel.
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Item type Current library Collection Call number URL Status Date due Barcode
Online Book (LOGIN USING YOUR MY CIU LOGIN AND PASSWORD) Online Book (LOGIN USING YOUR MY CIU LOGIN AND PASSWORD) G. Allen Fleece Library ONLINE HF1017 (Browse shelf(Opens below)) Link to resource Available BEP10483743
Online Book (LOGIN USING YOUR MY CIU LOGIN AND PASSWORD) Online Book (LOGIN USING YOUR MY CIU LOGIN AND PASSWORD) G. Allen Fleece Library Non-fiction HF1017 (Browse shelf(Opens below)) Link to resource Available 10483743

Includes index.

About the authors -- Chapter 1. Depicting data in telling ways -- Chapter 2. Summarizing location, scatter, and relative position -- Chapter 3. Understanding the normal distribution and the t- distribution -- Chapter 4. Using proof by contradiction to draw conclusions -- Chapter 5. Testing two population means and proportions -- Chapter 6. Analysis of variance from two or more populations -- Chapter 7. Testing proportions from two or more populations -- Chapter 8. Analyzing bivariate data -- Appendix. z-table, t-table, F table, and Chi-square table -- Index.

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Managers and analysts routinely collect and examine key performance measures to better understand their operations and make good decisions. Being able to render the complexity of operations data into a coherent account of significant events requires an understanding of how to work well with raw data and to make appropriate inferences. Although some statistical techniques for analyzing data and making inferences are sophisticated and require specialized expertise, there are methods that are understandable and applicable by anyone with basic algebra skills and the support of a spreadsheet package. By applying these fundamental methods themselves rather than turning over both the data and the responsibility for analysis and interpretation to an expert, managers will develop a richer understanding and potentially gain better control over their environment. This text is intended to describe these fundamental statistical techniques to managers, data analysts, and students. Statistical analysis of sample data is enhanced by the use of computers. Spreadsheet software is well suited for the methods discussed in this text. Examples in the text detail for the reader how to apply Microsoft Excel.

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Title from PDF t.p. (viewed on July 19, 2011).

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