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Essentials of business statistics / Bruce L. Bowerman, Miami University, Richard T. O'Connell, Miami University, Emily S. Murphree, Miami University, J. B. Orris, Butler University ; with major contributions by Steven C. Huchendorf, University of Minnesota, Dawn C. Porter, University of Southern California, Patrick J. Schur, Miami University.

Contributor(s): Material type: TextTextPublisher: New York : McGraw-Hill Education, 2015Edition: FIFTH EDITIONDescription: xxii, 633 pages : colored illustrations ; 29 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
  • online resource
ISBN:
  • 9780078020537 (alk. paper)
  • 0078020530 (alk. paper)
  • 9789814646383 (McGraw-Hill international ed.)
Subject(s): LOC classification:
  • HF 1017 .Es745 2015
Online resources:
Contents:
An introduction to business statistics -- Descriptive statistics: tabular and graphical methods -- Descriptive statistics: numerical methods -- Probability -- Discrete random variables -- Continuous random variables -- Sampling and sampling distributions -- Confidence intervals -- Hypothesis testing -- Statistical inferences based on two samples -- Experimental design and analysis of variance -- Chi-square tests -- Simple linear regression analysis -- Multiple regression and model building -- On website.
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Holdings
Item type Current library Collection Call number Copy number Status Date due Barcode
Reserved Books Reserved Books Tanay College Library Reserve Section Non-fiction HF 1017 .Es745 2015 (Browse shelf(Opens below)) 1 Available URSTAN-N2615

Includes bibliographic references (pages 626-627) index.

An introduction to business statistics -- Descriptive statistics: tabular and graphical methods -- Descriptive statistics: numerical methods -- Probability -- Discrete random variables -- Continuous random variables -- Sampling and sampling distributions -- Confidence intervals -- Hypothesis testing -- Statistical inferences based on two samples -- Experimental design and analysis of variance -- Chi-square tests -- Simple linear regression analysis -- Multiple regression and model building -- On website.

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