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Statistics for Management and Economics

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ISBN-10: 0534391656

ISBN-13: 9780534391652

Edition: 6th 2003

Authors: Gerald Keller, Brian Warrack

List price: $239.95
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STATISTICS FOR MANAGEMENT AND ECONOMICS is the worldwide best selling business statistics text. It is currently being used at hundreds of colleges and universities throughout the world. This text teaches students how to apply statistics to real business problems through the authors' unique three-step approach to problem solving. Students learn to IDENTIFY the right technique by focusing on the relationship between the problem and data type. They then learn to COMPUTE the answer either by hand, using Excel, or using MINITAB. Finally, they INTERPRET the results in the context of the problem. This approach enhances student comprehension as well as practical skills, and offers maximum…    
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Book details

List price: $239.95
Edition: 6th
Copyright year: 2003
Publisher: Cengage South-Western
Publication date: 7/1/2002
Binding: Hardcover
Pages: 1050
Size: 7.36" wide x 8.88" long x 1.30" tall
Weight: 3.982
Language: English

Dr. Gerald Keller is Emeritus Professor of Business at Wilfrid Laurier University, where he taught statistics, management science, and operations management from 1974 to 2011. He also taught at the University of Toronto, the University of Miami, McMaster University, the University of Windsor, and the Beijing Institute of Science and Technology. In addition to consulting with banks on credit scoring and credit card fraud, Dr. Keller has conducted market surveys for the Canadian government on energy conservation. His books include BSTAT, 2e, APPLIED STATISTICS WITH MICROSOFT EXCEL, ESSENTIALS OF BUSINESS STATISTICS (co-authored), AUSTRALIAN BUSINESS STATISTICS (co-authored), and STATISTICS…    

What is Statistics?
Introduction to Statistics
Key Statistical Concepts
Statistical Application in Business
Statistics and the Computer
World Wide Web and Learning Center
Introduction to Microsoft Excel
Introduction to Minitab
Graphical Descriptive Techniques
Types of Data and Information
Graphical Techniques for Interval Data
Graphical Techniques for Nominal Data
Describing the Relationship Between Two Variables
Describing Time-Series Data
Art and Science of Graphical Presentations
Introduction Graphical Excellence
Graphical Deception
Presenting Statistics
Numerical Descriptive Techniques
Measures of Central Location
Measures of Variability
Measures of Relative Standing and Box Plots
Measures of Linear Relationship
Comparing Graphical and Numerical Techniques
General Guidelines for Exploring Data
CD Topic: Approximating Means and Variances from Grouped Data
Review of Descriptive Techniques
CD Topic: Descriptive Techniques
Review Exercises
Data Collection and Sampling
Sources of Data
Sampling Plans
Sampling and Nonsampling Errors
Assigning Probability to Events
Joint, Marginal, and Conditional Probability
Probability Rules and Trees
Bayes' Law
Identifying the Correct Method
Random Variables and Discrete Probability Distributions
Random Variables and Probability Distributions
Describing the Population/Probability Distribution
Bivariate Distributions (optional)
Applications in Finance: Investment Portfolio Diversification and Asset Allocations (optional)
Binomial Distribution
Poisson Distribution (optional)
CD Topic: Hypergeometric Distribution
Continuous Probability Distributions
Continuous Probability Distributions
Normal Distribution
Exponential Distribution (optional)
Other Continuous Distributions
Sampling Distributions
Sampling Distribution of the Mean
Sampling Distribution of a Proportion
Sampling Distribution of the Difference between Two Means
From Here to Inference
CD Topic: Using the Laws of Expected Value and Variance to Derive the Parameters of Sampling Distributions
Introduction to Estimation
Concepts of Estimation
Estimating the Population Mean when the Population Standard Deviation is Known
Selecting the Sample Size
Introduction to Hypothesis Testing
Concepts of Hypothesis Testing
Testing the Population Mean when the Population Standard Deviation is Known
Calculating the Probability of a Type II Error
The Road Ahead
Inference About One Population
Inference about a Population Mean when the Standard Deviation is Unknown
Inference about a Population Variance
Inference about a Population Proportion
Applications in Marketing: Market Segmentation
CD Topic: Probability of a Type II Error in Testing Proportions
Inference About Two Populations
Inference about the Difference between Two Means: Independent Samples
Observational and Experimental Data
Inference about the Difference between Two Means: Matched Pairs Experiment
Inference about the Ratio of Two Variances
Inference about the Difference between Two Population Proportions
Excel Instructions for Stacked and Unstacked Data
MINITAB Instructions for Stacked and Unstacked Data
CD Topic: Probability of a Type II Error in Testing Two Means
CD Topic: Probability of a Type II Error in Testing Two Proportions
Review of Chapters 12 and 13
Guide to Identifying the Correct Technique: Chapters 12 and 13
Analysis of Variance
One Way Analysis of Variance
Analysis of Variance Experimental Designs
Randomized Blocks (Two-Way) Analysis of Variance
Two-Factor Analysis of Variance
Applications in Operations Management: Finding and Reducing Variation
Multiple Comparisons
CD Topic: Bartlett's Test
Chi-Square Tests
Chi-Square Goodness-of-Fit Test
Chi-Square Test of a Contingency Table
Summary of Tests on Nominal Data
Chi-Square Test for Normality (optional)
CD Topic: Rule of Five
CD Topic: Minitab Instructions
Nonparametric Statistics Techniques
Wilcoxon Rank Sum Test
Sign Test and Wilcoxon Signed Rank Sum Test
Kruskal-Wallis Test
Friedman Test
CD Topic: Lillifors' Test
Mann-Whitney Test
Simple Linear Regression
Estimating the Coefficients
Error Variable: Required Conditions
Assessing the Model
Applications in Finance: Market Model (optional)
Using the Regression Equation
Coefficients of Correlation
Regression Diagnostics I. Summary
CD Topic: Deriving the Formulas that Estimate the Coefficients
Multiple Regression
Model and Required Conditions
Estimating the Coefficients and Assessing the Model
Regression Diagnostics II
Regression Diagnostics III (Time Series)
CD Topic: Transformations
Model Building
Polynomial Models
Nominal Independent Variables
Applications in Human Resource Management: Pay Equity
Stepwise Regression
Model Building
CD Topic: Regression and the Analysis of Variance
Time Series Analysis and Forecasting
Time Series Components
Smoothing Techniques
Trend and Seasonal Effects
Introduction to Forecasting
Forecasting Models
CD Topic: Index Numbers
Statistical Process Control
Process Variation
Control Charts
Control Charts for Variables: x-bar and S Charts
Control Charts for Attributes: p Chart
CD Topic: Control Charts for variables: x-bar and R Charts
Decision Analysis
Decision Problem
Acquiring, Using and Evaluating Additional Information
CD Topic: Treeplan
Statistical Inference: Conclusion
Identifying the Correct Technique: Summary of Statistical Inference
The Last Word
Data File Sample Statistics
Answers to Selected Even-Numbered Exercises