Final Review
This excellent book will guide you into the area of micro economics.
It not just because of wonderful design and pretty pictures that
this book gets such good reviews.
I have tested the complete book by reading from front to back and
assessing my knowledge by passing a simulated academic test. Key
areas are explained and you get enough diagrams to understand the
way shortages and surpluses affect the economy. But as I noticed
being tired after a long working day, I needed to exercise my understanding
by using the offered study guide.
I have enjoyed this book and expanded my knowledge at a high quality
level. This is a real A+ Quality for Money Product. It is certainly
a large, heavy book but the paper, the print and cover are well
produced.
I personally can only recommend this book to any freshman at english
speaking universities. I understand that many universites in the
US and Australia use this as a basis to train their students.
New to the Edition
Updated CD-ROM packaged with every textbook. The most recent versions
of StatPro, @Risk, Precision Tree, Best Fit, RISKView, Top Rank,
and Solver Table along with data files, and appendices are included
on the CD-ROM.
New pedagogical features explain concepts even more clearly at
the outset, especially in the statistics chapters. New features
include: margin notes, boxed-in definitions (and formulas) in the
text, enhanced explanations in the text itself, and stated objectives
for the examples.
A list of key terms and formulas appears at the end of each chapter
to make it easier for students to study and for instructors to teach.
The book is now divided into PARTS: Part I: Getting, Describing,
and Summarizing Data (Chapters 2-4); Part II: Probability, Uncertainty,
and Decision Making (Chapters 5-7); Part III: Statistical Inference
(Chapters 8-10); Part IV: Regression, Time Series, and Forecasting
(Chapters 11-13); and Part V: Decision Modeling (Chapters 14-16).
This provides a clearer view of the organization of the book.
The data for many of the problems have been updated to be as timely
as possible. This is specifically true for time series data. Many
of the data sets now end in 2000 or 2001.
The conceptual exercises at the end of each chapter wither test
the concepts or ask more open-ended questions - as opposed to the
many number-crunching problems already in the book.
Chapter 4 Getting The Right Data is new and deals with getting
the right data into Excel for analysis. This includes discussion
of Excel's own database tools, getting data from an external database
such as Access into Excel, and getting data from the Web into Excel.
It also includes sections on sources of data and cleansing data.
Chapter 5, Probability and Probability Distributions, has been
revised significantly. The more advanced examples have been simplified
or eliminated.
Chapter 6, Normal, Binomial, Poisson, and Exponential Distributions,
now contains a brief discussion of the exponential distribution.
Chapter 8, Sampling and Sampling Distributions, has been reorganized
significantly, increasing the strength and logic of the conceptual
development.
Chapter 10, Hypothesis Testing, now has a section on the chi-square
test for independence (which can be carried out with StatPro).
Chapter 13, Time Series Analysis and Forecasting, has been entirely
reorganized. As examples, there is now an introductory section on
the various components of a time series (level, trend, seasonality,
and noise), and the techniques for handling seasonality are all
contained in a single section.
About the Author
S. Christian Albright
Chris Albright received his B.S. degree in Mathematics from Stanford
in 1968 and his Ph.D. in Operations Research from Stanford in 1972.
Since then, he has been teaching in the Operations and Decision
Technologies Department in the Kelley School of Business at Indiana
University. He has taught courses in management science, computer
simulation, and statistics to all levels of business students: undergraduates,
MBAs, and doctoral students. He has published over 20 articles in
leading operations research journals in the area of applied probability,
and he has authored other successful Duxbury titles including PRACTICAL
MANAGEMENT SCIENCE, Second Edition, VBA FOR MODELERS, and DATA ANALYSIS
AND DECISION MAKING, Second Edition. His current interest is in
spreadsheet modeling, including development of VBA applications
in Excel.
Wayne Winston
Wayne L. Winston is Professor of Operations and Decision Technologies
in the Kelley School of Business at Indiana University, where he
has taught since 1975. Wayne received his B.S. degree in Mathematics
from MIT and his Ph.D. degree in Operations Research from Yale.
He has written the successful textbooks OPERATIONS RESEARCH: APPLICATIONS
AND ALGORITHMS, MATHEMATICAL PROGRAMMING: APPLICATIONS AND ALGORITHMS,
SIMULATION MODELING WITH @RISK, PRATICAL MANAGEMENT SCIENCE, AND
FINANCIAL MODELS USING SIMULATION AND OPTIMIZATION. Wayne has published
over 20 articles in leading journals and has won many teaching awards,
including the school-wide MBA award four times. His current interest
is in showing how spreadsheet models can be used to solve business
problems in all disciplines, particularly in finance and marketing.
Christopher Zappe
Chris Zappe earned his BA in mathematics from DePauw University
in 1983 and his MBA and Ph.D. in Decision Sciences from Indiana
University in 1987 and 1988, respectively. Between 1988 and 1993,
he performed research and taught various courses in the decision
sciences area at the University of Florida in the College of Business
Administration. Since 1993, Chris has been serving as an associate
professor of decision sciences in the Department of Management at
Bucknell University. He currently teaches undergraduate courses
in business statistics, decision analysis, and computer simulation.
Moreover, Chris teaches advanced seminars in applied game theory,
system dynamics, risk assessment, and mathematical economics. He
has published articles in various journals including Managerial
and Decision Economics, OMEGA, Naval Research Logistics, and Interfaces,
and is co-author of DATA ANALYSIS AND DECISION MAKING. His current
scholarly interests focus on mathematical programming models of
performance appraisal processes and innovative pedagogies in operations
research/management science.
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