UOWD Library

Introduction to business analytics using simulation (Record no. 29499)

000 -LEADER
fixed length control field 05236nam a2200241 a 4500
FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160628n 000 0 eng d
INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780128104842
DATE AND TIME OF LATEST TRANSACTION
control field 20170126101148.0
CONTROL NUMBER
control field 64491
CONTROL NUMBER IDENTIFIER
control field UOWD
MAIN ENTRY--PERSONAL NAME
Personal name Pinder, Jonathan P.
TITLE STATEMENT
Title Introduction to business analytics using simulation
Statement of responsibility, etc Jonathan P.Pinder
PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Amsterdam :
Name of publisher, distributor, etc Academic Press, Elsevier Science & Technology Books,
Date of publication, distribution, etc c2017.
PHYSICAL DESCRIPTION
Extent xiii, 434 p. :
Other physical details ill. ;
Dimensions 24 cm.
SUMMARY, ETC.
Summary, etc Introduction to Business Analytics using Simulation employs an innovative strategy to teach business analytics. It uses simulation modeling and analysis as mechanisms to introduce and link predictive and prescriptive modeling. Because managers do not know what will happen in the future but must make decisions, it treats uncertainty as an essential element in decision-making. Its use of simulation gives readers a superior way of analyzing past data, understanding an uncertain future, and optimizing results to select the best decision. With its focus on the uncertainty and variability of business, Introduction to Business Analytics Using Simulation provides a better foundation for business analytics than standard introductory business analytics books. Students gain a better understanding of fundamental statistical concepts that are essential to marketing research, Six-Sigma, financial analysis, and business analytics. Teaches how managers use business analytics to formulate and solve business problems and to support managerial decision making Explains the processes needed to develop, report, and analyze business data Describes how to use and apply business analytics software Includes 50 caselettes, quizzes for each exercise set, a quiz generator spreadsheet, and a sample syllabus.
FORMATTED CONTENTS NOTE
Formatted contents note Cover ; Title Page; Copyright Page; Contents; Preface; Acknowledgments; Chapter 1 -- Business analytics is making decisions; Introduction; 1.1 -- Business Analytics is making decisions subject to uncertainty; 1.2 -- Components of Business Analytics; 1.3 -- Uncertainty = probability = stochastic; 1.4 -- What is simulation?; 1.4.1 -- Why Use Simulation?; 1.4.2 -- Simulation Applications; 1.5 -- Monte Carlo simulation and random variables; 1.6 -- Simulation terminology; 1.7 -- Probability as relative frequency; 1.8 -- Overview of simulation process; 1.9 -- Random number generation in Excel 1.10 -- Extra practiceChapter 2 -- Decision-making and simulation; Introduction; 2.1 -- Introduction to decision-making; 2.1.1 -- Define the Problem; 2.1.2 -- Identify and Weight the Criteria; 2.1.3 -- Generate Alternatives; 2.1.4 -- Evaluate Each Alternative; 2.1.5 -- Compute the Optimal Decision; 2.2 -- Probability: the measure of uncertainty; 2.3 -- Where do the probabilities come from?; 2.4 -- Elements of probability; 2.5 -- Probability notation; 2.6 -- Examples of simulation and decision-making; Chapter 3 -- Decision Trees; Introduction; 3.1 -- Decision trees and expected value 3.2 -- Properties of decision trees3.2.1 -- Linear Transforms; 3.3 -- Overview of the decision making process; 3.4 -- Sensitivity analysis; 3.5 -- Expected value of perfect information; 3.6 -- Summary of the decision analysis process; Chapter 4 -- Probability: measuring uncertainty; Introduction; 4.1 -- Probability: measuring likelihood; 4.2 -- Probability distributions; 4.3 -- General probability rules; 4.4 -- Conditional probability and Bayes' theorem; Further exercises: common interview questions regarding probability; Chapter 5 -- Subjective Probability Distributions; Introduction 5.1 -- Subjective probability distributions-probability from experience5.2 -- Two-point estimation: uniform distribution; 5.2.1 -- Discrete Uniform Distribution; 5.3 -- Three-point estimation: triangular distribution; 5.3.1 -- Simulating a Symmetric Triangular Distribution; 5.3.2 -- Simulating an Asymmetric Triangular Distribution; 5.4 -- Five-point estimates for subjective probability distributions; 5.4.1 -- Simulating a Five-Point Distribution; 5.4.2 -- Other Estimates for Subjective Probability Distributions; Chapter 6 -- Empirical probability distributions; Introduction 6.1 -- Empirical probability distributions-probability from data6.2 -- Discrete empirical probability distributions; 6.3 -- Continuous empirical probability distributions; Chapter 7 -- Theoretical probability distributions; Introduction; 7.1 -- Theoretical/classical probability; 7.2 -- Review of notation for probability distributions; 7.3 -- Discrete theoretical distributions; 7.3.1 -- Uniform Distribution; 7.3.2 -- Discrete Uniform Distribution; 7.3.3 -- Continuous Uniform Distribution; 7.3.4 -- Bernoulli Distribution; 7.3.5 -- Binomial Distribution; 7.3.6 -- Poisson distribution 7.4 -- Continuous probability distributions
SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Business intelligence
Source of heading or term sears
SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Business
General subdivision Computer simulation
Source of heading or term sears
SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Industrial management
General subdivision Statistical methods
Source of heading or term sears
SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element BUSINESS & ECONOMICS / Industrial Management
Source of heading or term sears
SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element BUSINESS & ECONOMICS / Management Science
Source of heading or term sears
ADDED ENTRY ELEMENTS (KOHA)
Koha item type REGULAR
Holdings
Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent Location Current Location Shelving location Date acquired Source of acquisition Full call number Barcode Date last seen Cost, replacement price Price effective from Koha item type
        University of Wollongong in Dubai University of Wollongong in Dubai MAIN 2016-10-11 AMAUK 658.40352 PI IN T0037112 2017-01-26 60.69 2017-01-26 REGULAR
        University of Wollongong in Dubai University of Wollongong in Dubai MAIN 2016-10-31 AMAUK 658.40352 PI IN T0054642 2017-01-26 331.00 2017-01-26 REGULAR

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