Basic Statistical Ideas for Managers

ISBN-10: 0534378056

ISBN-13: 9780534378059

Edition: 2nd 2005 (Revised)

Authors: R. Lyman Ott, J. Brian Gray, David Hildebrand

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Description:

Designed for the one-term MBA or undergraduate introduction to business statistics course, this text places emphasis on data and the common techniques and methods used to analyze them in business. It introduces concepts using practical examples and illustrates them with computer output from MINITAB, Excel, and JMP. The book integrates a business decision-making case into each chapter for motivational and illustration purposes and includes a business case assignment at the end of each chapter. These cases revolve around realistic business settings with realistic data sets that put students in the role of managers who need to make business decisions based on data. Review problems requiring students to use previously learned concepts also appear throughout to promote understanding of the relationships among statistical methods.
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Book details

List price: $324.95
Edition: 2nd
Copyright year: 2005
Publisher: Brooks/Cole
Publication date: 6/4/2004
Binding: Paperback
Pages: 792
Size: 8.27" wide x 10.24" long x 1.38" tall
Weight: 3.894

J. Brian Gray is Professor of Statistics in the Applied Statistics Program and in the Department of Information Systems, Statistics, and Management Science at The University of Alabama, where he teaches a variety of statistics courses at the undergraduate, masters, and doctoral levels. Dr. Gray has taught MBA and Executive MBA statistics courses for the past 20 years and has received several teaching awards from the MBA and Executive MBA Associations of The University of Alabama and Texas Christian University. He co-authored the book BUSINESS CASES IN STATISTICAL DECISION-MAKING: COMPUTER BASED APPLICATIONS. Dr. Gray is an active member of the American Statistical Association. His current research interests are in the areas of applied statistics, exploratory data analysis, data mining, regression analysis, statistical computing, and graphics. He has published research articles in journals including TECHNOMETRICS, JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, THE AMERICAN STATISTICIAN, COMPUTATIONAL STATISTICS AND DATA ANALYSIS, JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, STATISTICS AND COMPUTING, JOURNAL OF REAL ESTATE RESEARCH, and JOURNAL OF BUSINESS, FINANCE, & ACCOUNTING. Dr. Gray received the Wilcoxon Prize for Best Practical Application Paper in TECHNOMETRICS in 1984.

Making Sense of Data
Executive Overview
What Do We Mean by "Data?"
Data About What?Gathering Data
Summarizing Data
The Role of Probability
Evaluating Other People''s Data and Conclusions
The Role of theComputer
Summary
Summarizing Data
Executive Overview
Chapter Case Introduction
The Distribution ofValues of a Variable
Two-Variable Summaries
On the Average:Typical Values
Measuring Variability
Calculators and StatisticalSoftware
Statistical Methods and Quality Improvement
ChapterCase Analyses
Summary
Supplementary Exercises
Business Cases
A First Look at Probability
Executive Overview
Chapter Case Introduction
Basic Principles ofProbability
Statistical Independence
Probability Tables, Trees, andSimulations
Chapter Case Analysis
Summary
SupplementaryExercises
Business Cases
Review Exercises: Chapters 2 and 3
Random Variables and Probability Distribution
Executive Overview
Chapter Case Introduction
Random Variables:Basic Ideas
Probability Distributions: Discrete Random Variables
Expected Value, Variance, and Standard Deviation
Joint ProbabilityDistributions and Independence
Covariance and Correlation ofRandom Variables
Chapter Case Analysis
Summary
SupplementaryExercises
Business Cases
Some Special Probability Distributions
Executive Overview
Chapter Case Introduction
Counting PossibleOutcomes
Bernoulli Trials and the Binomial Distribution
ThePoisson Distribution
The Normal Distribution
Checking Normality
Chapter Case Analysis
Summary
Supplementary Exercises
BusinessCases
Random Sampling and Sampling Distrubtions
Executive Overview
Chapter Case Introduction
Random Sampling
Sample Statistics and Sampling Distributions
SamplingDistributions for Means and Sums
Chapter Case Analysis
Summary
Appendix: Standard Error of a Mean
Supplementary Exercises
Business Cases
Review Exercises: Chapters 4-6
Point Interval Estimation
Executive Overview
Chapter Case Introduction
Point Estimators
Interval Estimation of a Mean, Known Standard Deviation
ConfidenceIntervals for a Proportion
How Large a Sample is Needed?
The tDistribution
Confidence Intervals with the t Distribution
Assumptions for Interval Estimation
Chapter Case Analysis
Summary
Supplementary Exercises
Business Case
Hypothesis Testing
Executive Overview
Chapter Case Introduction
A Test for a Mean,Known Standard Deviation
Type II Error, � Probability, and Power ofa Test
The p-Value for a Hypothesis Test
Hypothesis Testing withthe t Distribution
Assumptions for t Tests
Testing a Proportion:Normal Approximation
Hypothesis Tests and Confidence Intervals
Chapter Case Analysis
Summary
Supplementary Exercises
BusinessCase
Review Exercises: Chapters 7-8
Comparing Two Samples
Executive Overview
Chapter Case Introduction
Comparing the Means of Two Populations
ANonparametric Test: The Wilcoxon Rank SumTest
Paired-Sample Methods
TheSigned-Rank Method
Two-SampleProcedures for Proportions
Chi-Squared Test for CountData
Chapter Case Analysis
Summary
Supplementary Exercises
Business Cases
Analysis of Variance and Designedexperiments
Executive Overview
Chapter Case Introduction
Testing the Equality of Several PopulationMeans
Comparing Several Distributions by a Rank Test
SpecificComparisons Among Means
Two-Factor Experiments
RandomizedBlock Designs
Chapter Case Analysis
Summary
SupplementaryExercises
Business Cases
Linear Regression and Correlation Methods
Executive Overview
Chapter Case Introduction
The LinearRegression Model
Estimating Model Parameters
Inferences aboutRegression Parameters
Predicting New Y Values using Regression
Correlation
Chapter Case Analysis
Summing Up
SupplementaryExercises
Business Cases
Multiple Regression Methods
Executive Overview
Chapter Case Introduction
The MultipleRegression Model
Estimating Multiple Regression Coefficients
Inferences in Multiple Regression
Testing a Subset of theRegression Coefficients
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