Basic Statistics for Business and Economics

ISBN-10: 0073121657
ISBN-13: 9780073121659
Edition: 5th 2006
List price: $154.69
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Description: The Fifth Edition of Basic Statistics for Business and Economics is a shorter version of Lind/Marchal/Wathen's Statistical Techniques in Business and Economics, 12e. The authors of this text continue to provide a student-oriented approach to  More...

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Book details

List price: $154.69
Edition: 5th
Copyright year: 2006
Publisher: McGraw-Hill Higher Education
Binding: Mixed Media
Pages: 558
Size: 8.00" wide x 10.50" long x 1.25" tall
Weight: 2.882
Language: English

The Fifth Edition of Basic Statistics for Business and Economics is a shorter version of Lind/Marchal/Wathen's Statistical Techniques in Business and Economics, 12e. The authors of this text continue to provide a student-oriented approach to business statistics. In this book you will find step-by-step solved examples, realistic exercises, and up-to-date technology and illustrations. Book jacket.

Douglas A. Lind is now an adjunct professor at Coastal Carolina University. He earned his Ph.D. and an MBA from The University of Toledo and a Bachelor of Science in Business from Bowling Green State University.Dr. Lind is the co-author with the late Robert D. Mason and William G. Marchal of Statistical Techniques in Business and Economics and Basic Statistics for Business and Economics published by Irwin/McGraw-Hill and Statistics: An Introduction published by Duxbury. In addition he has written Study Guides to be used with these texts.Dr. Lind has more than 25 years of college teaching experience. This includes teaching statistics at the introductory, intermediate, and advanced undergraduate level, as well as graduate courses in statistics and research methods. He is a past recipient of the Tony DeJute Outstanding Teacher award. This award is given annually by the College of Business to the outstanding teacher in the College.He is active in both consulting and community service in Northwest Ohio. He has consulted with such national firms as Ford Motor Company, Key Bank, National City Bank, and the former Sheller Globe. Regional consulting includes work with The Toledo Hospital, St. Vincent Mercy Medical Center, and the Toledo Community Oncology Program. He has served the community of Perrysburg, Ohio as a member of volunteer committees for the city and the school system. This includes his most avid avocation, coaching high school baseball, having served as a volunteer coach for more than 12 years.His professional memberships include The American Statistical Association, Decision Sciences, and The Textbook Author's Association.

William G. Marchal is Professor of Information Systems and Operations Management at The University of Toledo College of Business Administration. He received his B.S. degree in Mathematics from The University of Dayton, an M.A. in Mathematics from The Catholic University of America, and his D. Sc. in Operations Research from The George Washington University. Dr. Marchal has held visiting appointments at The University of Michigan and George Mason University. He has also worked at the Executive Office of the District of Columbia government, the George Washington University Institute for Management Science, and the U.S. Army Chemical Research & Development Center.Dr. Marchal is co-author with the late Robert D. Mason and Douglas A. Lind of three textbooks: Statistics: An Introduction; Statistical Techniques in Business & Economics; and Basic Statistics for Business & Economics. His research on stochastic models focuses on applications to waiting line models. Dr. Marchal has made paper presentations at meetings of professional societies, referred papers for journals and served as an associate editor of Naval Research Logistics. Published articles appear in the journals: Communications in Statistics, INFORMS, Journal on Computing, IIE Transactions, Interfaces, Operations Research, The Annals of Operations Research, AIIE Transactions and The Journal of Applied Probability.

Samuel Wathen is a Professor in the E. Craig Wall Sr. College of Business Administration at Coastal Carolina University. He earned his Ph.D. in Business Administration from the University of Minnesota, a M.B.A. from Oklahoma State University, a M.S. in Forest Biometrics from Virginia Polytechnic Institute and State University, and a B.S. in Forestry from the University of Illinois. Dr. Wathen's research interests include applied statistics, teaching methods, and manufacturing and service process design. He has published articles in the International Journal of Operations and Production Management, National Productivity Review, International Journal of Service Industry Management, and the Journal of Workplace Learning: Employee Counseling Today. Dr. Wathen has 14 years of teaching experience. This includes introductory statistics, decision analysis, operations management, materials management, and service operations management. His experience spans both graduate and undergraduate programs. He attended a Master Teaching seminar held at Georgia State University that offered concepts and techniques to improve course design, course delivery, exam construction, student involvement, and many other aspects of teaching.

What Is Statistics?
Introduction
Why Study Statistics?
What Is Meant by Statistics?
Types of Statistics
Descriptive Statistics
Inferential Statistics
Types of Variables
Levels of Measurement
Nominal-Level Data
Ordinal-Level Data
Interval-Level Data
Ratio-Level Data
Exercises
Statistics, Graphics, and Ethics
Misleading Statistics
Association Does Not Necessarily Imply Causation
Graphs Can Be Misleading
Become a Better Consumer and a Better Producer of Information
Ethics
Software Applications
Chapter Outline
Chapter Exercises
exercises.com
Dataset Exercises
Answers to Self-Review
Describing Data: Frequency Distributions and Graphic Presentation
Introduction
Constructing a Frequency Distribution
Class Intervals and Class Midpoints
A Software Example
Relative Frequency Distribution
Exercises
Graphic Presentation of a Frequency Distribution
Histogram
Frequency Polygon
Exercises
Cumulative Frequency Distributions
Exercises
Other Graphic Presentations of Data
Line Graphs
Bar Charts
Pie Charts
Exercises
Chapter Outline
Chapter Exercises
exercises.com
Dataset Exercises
Software Commands
Answers to Self-Review
Describing Data: Numerical Measures
Introduction
The Population Mean
The Sample Mean
Properties of the Arithmetic Mean
Exercises
The Weighted Mean
Exercises
The Median
The Mode
Exercises
Software Solution
The Relative Positions of the Mean, Median, and Mode
Exercises
The Geometric Mean
Exercises
Why Study Dispersion?
Measures of Dispersion
Range
Mean Deviation
Exercises
Variance and Standard Deviation
Exercises
Software Solution
Exercises
Interpretation and Uses of the Standard Deviation
Chebyshev's Theorem
The Empirical Rule
Exercises
Chapter Outline
Pronunciation Key
Chapter Exercises
exercises.com
Dataset Exercises
Software Commands
Answers to Self-Review
Describing Data: Displaying and Exploring Data
Introduction
Dot Plots
Exercises
Quartiles, Deciles, and Percentiles
Exercises
Box Plots
Exercises
Skewness
Exercises
Describing the Relationship between Two Variables
Exercises
Chapter Outline
Pronunciation Key
Chapter Exercises
exercises.com
Dataset Exercises
Software Commands
Answers to Self-Review
A Survey of Probability Concepts
Introduction
What Is a Probability?
Approaches to Assigning Probabilities
Classical Probability
Empirical Probability
Subjective Probability
Exercises
Some Rules for Computing Probabilities
Rules of Addition
Exercises
Rules of Multiplication
Contingency Tables
Tree Diagrams
Exercises
Principles of Counting
The Multiplication Formula
The Permutation Formula
The Combination Formula
Exercises
Chapter Outline
Pronunciation Key
Chapter Exercises
exercises.com
Dataset Exercises
Software Commands
Answers to Self-Review
Discrete Probability Distributions
Introduction
What Is a Probability Distribution?
Random Variables
Discrete Random Variable
Continuous Random Variable
The Mean, Variance, and Standard Deviation of a Probability Distribution
Mean
Variance and Standard Distribution
Exercises
Binomial Probability Distribution
How Is a Binomial Probability Distribution Computed
Binomial Probability Tables
Exercises
Cumulative Binomial Probability Distributions
Exercises
Poisson Probability Distribution
Exercises
Chapter Outline
Chapter Exercises
Dataset Exercises
Software Commands
Answers to Self-Review
Continuous Probability Distributions
Introduction
The Family of Uniform Distributions
Exercises
The Family of Normal Probability Distributions
The Standard Normal Distribution
The Empirical Rule
Exercises
Finding Areas under the Normal Curve
Exercises
Exercises
Exercises
Chapter Outline
Chapter Exercises
Dataset Exercises
Software Commands
Answers to Self-Review
Sampling Methods and the Central Limit Theorem
Introduction
Sampling Methods
Reasons to Sample
Simple Random Sampling
Systematic Random Sampling
Stratified Random Sampling
Cluster Sampling
Exercises
Sampling "Error"
Sampling Distribution of the Sample Mean
Exercises
The Central Limit Theorem
Exercises
Using the Sampling Distribution of the Sample Mean
Exercises
Chapter Outline
Pronunciation Key
Chapter Exercises
exercises.com
Dataset Exercises
Software Commands
Answers to Self-Review
Estimation and Confidence Intervals
Introduction
Point Estimates and Confidence Intervals
Known [sigma] or a Large Sample
A Computer Simulation
Exercises
Unknown Population Standard Deviation and a Small Sample
Exercises
A Confidence Interval for a Proportion
Exercises
Finite-Population Correction Factor
Exercises
Choosing an Appropriate Sample Size
Exercises
Chapter Outline
Pronunciation Key
Chapter Exercises
exercises.com
Dataset Exercises
Software Commands
Answers to Self-Review
One-Sample Tests of Hypothesis
Introduction
What Is a Hypothesis?
What Is Hypothesis Testing?
Five-Step Procedure for Testing a Hypothesis
State the Null Hypothesis (H[subscript 0]) and the Alternate Hypothesis (H[subscript 1])
Select a Level of Significance
Select the Test Statistic
Formulate the Decision Rule
Make a Decision
One-Tailed and Two-Tailed Tests of Significance
Testing for a Population Mean with a Known Population Standard Deviation
A Two-Tailed Test
A One-Tailed Test
p-Value in Hypothesis Testing
Testing for a Population Mean: Large Sample, Population Standard Deviation Unknown
Exercises
Tests Concerning Proportions
Exercises
Testing for a Population Mean: Small Sample, Population Standard Deviation Unknown
Exercises
A Software Solution
Exercises
Chapter Outline
Pronunciation Key
Chapter Exercises
exercises.com
Dataset Exercises
Software Commands
Answers to Self-Review
Two-Sample Tests of Hypothesis
Introduction
Two-Sample Tests of Hypothesis: Independent Samples
Exercises
Two-Sample Tests about Proportions
Exercises
Comparing Population Means with Small Samples
Exercises
Two-Sample Tests of Hypothesis: Dependent Samples
Comparing Dependent and Independent Samples
Exercises
Chapter Outline
Pronunciation Key
Chapter Exercises
exercises.com
Dataset Exercises
Software Commands
Answers to Self-Review
Analysis of Variance
Introduction
The F Distribution
Comparing Two Population Variances
Exercises
ANOVA Assumptions
The ANOVA Test
Exercises
Inferences about Pairs of Treatment Means
Exercises
Chapter Outline
Pronunciation Key
Chapter Exercises
exercises.com
Dataset Exercises
Software Commands
Answers to Self-Review
Linear Regression and Correlation
Introduction
What Is Correlation Analysis?
The Coefficient of Correlation
The Coefficient of Determination
Correlation and Cause
Exercises
Testing the Significance of the Correlation Coefficient
Exercises
Regression Analysis
Least Squares Principle
Drawing the Line of Regression
Exercises
The Standard Error of Estimate
Assumptions Underlying Linear Regression
Exercises
Confidence and Prediction Intervals
Exercises
More on the Coefficient of Determination
Exercises
The Relationships among the Coefficient of Correlation, the Coefficient of Determination, and the Standard Error of Estimate
Transforming Data
Exercises
Chapter Outline
Pronunciation Key
Chapter Exercises
exercises.com
Dataset Exercises
Software Commands
Answers to Self-Review
Multiple Regression and Correlation Analysis
Introduction
Multiple Regression Analysis
Inferences in Multiple Linear Regression
Exercises
Multiple Standard Error of Estimate
Assumptions about Multiple Regression and Correlation
The ANOVA Table
Exercises
Evaluating the Regression Equation
Using a Scatter Diagram
Correlation Matrix
Global Test: Testing the Multiple Regression Model
Evaluating Individual Regression Coefficients
Qualitative Independent Variables
Exercises
Analysis of Residuals
Chapter Outline
Pronunciation Key
Chapter Exercises
exercises.com
Dataset Exercises
Software Commands
Answers to Self-Review
Chi-Square Applications
Introduction
Goodness-of-Fit Test: Equal Expected Frequencies
Exercises
Goodness-of-Fit Test: Unequal Expected Frequencies
Limitations of Chi-Square
Exercises
Contingency Table Analysis
Exercises
Chapter Outline
Pronunciation Key
Chapter Exercises
exercises.com
Dataset Exercises
Software Commands
Answers to Self-Review
CD Chapters
Statistical Quality Control
Time Series and Forecasting
Appendixes
Tables
Binomial Probability Distribution
Critical Values of Chi-Square
Poisson Distribution
Areas under the Normal Curve
Table of Random Numbers
Student's t Distribution
Critical Values of the F Distribution
Wilcoxon T Values
Factors for Control Charts
Datasets
Real Estate
Major League Baseball
Wages and Wage Earners
CIA International Economic and Demographic Data
Whitner Autoplex
Getting Started with Megastat
Visual Statistics
Answers to Odd-Numbered Exercises
Photo Credits
Index

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