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Statistics for Management and Economics

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ISBN-10: 0538477490

ISBN-13: 9780538477499

Edition: 9th 2012

Authors: Gerald Keller

List price: $324.95
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Book details

List price: $324.95
Edition: 9th
Copyright year: 2012
Publisher: Cengage South-Western
Publication date: 1/1/2011
Binding: Hardcover
Pages: 1008
Size: 8.00" wide x 10.00" long x 0.75" tall
Weight: 1.232
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?
Key Statistical Concepts
Statistical Applications in Business
Statistics and the Computer
World Wide Web and Learning Center
Instructions for the CD-ROM
Graphical Descriptive Techniques I
Types of Data and Information
Describing a Set of Nominal Data
Describing the Relationship between Two Nominal Variables and Comparing Two or More Nominal Data Sets
Graphical Descriptive Techniques II
Graphical Techniques to Describe a Set of Interval Data
Describing Time-Series Data
Describing the Relationship between Two Interval Variables
Art and Science of Graphical Presentations
Numerical Descriptive Techniques
Measures of Central Location
Measures of Variability
Measures of Relative Standing and Box Plots
Measures of Linear Relationship
(Options) Applications In Professional Sports: Baseball
(Optional) Applications In Finance: Market Model
Comparing Graphical and Numerical Techniques
General Guidelines for Exploring Data
Review Of chapters 2 to 4
Data Collection and Sampling
Methods of Collecting Data
Sampling
Sampling Plans
Sampling and Nonsampling Errors
Probability
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
Bivariate Distributions
(Optional) Applications In Finance: Investment Portfolio Diversification and Asset Allocation
Binomial Distribution
Poisson Distribution
Continuous Probability Distributions
Probability Density Functions
Normal Distribution
(Optional) Exponential Distribution
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
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
(Optional) Applications In Marketing: Market Segmentation
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
Review of Chapters 12 and 13
Analysis of Variance
One Way Analysis of Variance
Multiple Comparisons
Analysis of Variance Experimental Designs
Randomized Blocks (Two Way) Analysis of Variance
Two-Factor Analysis of Variance
(Optional) Applications In Operations Management: Finding and Reducing Variation
Review of chapters 12 to 14
Chi-Squared Tests
Chi-Squared Goodness-of-Fit Test
Chi-Squared Test of a Contingency Table
Summary of Tests on Nominal Data
(Optional) Chi-Squared Test for Normality
Review of Chapters 12 to 15
Simple Linear Regression
Model
Estimating the Coefficients
Error Variable: Required Conditions
Assessing the Model
Using the Regression Equation
Regression Diagnostics - I
Review of Chapters 12 to 16
Multiple Regression
Model and Required Conditions
Estimating the Coefficients and Assessing the Model
Regression Diagnostics - II
Regression Diagnostics- III (Time Series)
Review of Chapters 12 to 17
Model Building
Polynomial Models
Nominal Independent Variables
(Optional) Applications In Human Resources Management: Pay Equity
Logistic Regression
Stepwise Regression
Model Building
Nonparametric Statistical Techniques
Wilcoxon Rank Sum Test
Sign Test and Wilcoxon Signed Rank Sum Test
Kruskal-Wallis Test
Friedman Test
Spearman Rank Correlation
Review of Chapters 12 to 19
Time-Series Analysis and Forecasting
Time Series Components
Smoothing Techniques
Trend and Seasonal Effects
Introduction to Forecasting
Forecasting Models
Statistical Process Control. 21.1.Process Variation
Control Charts
Control Charts for Variables: and S Charts
Control Charts for Attributes: p Chart. 22:Decision Analysis
Decision Problem
Acquiring, Using and Evaluating Additional Information
Conclusion
Data File Sample Statistics
Tables
Binomial Probabilities
Poisson Probabilities
Normal Probabilities
Critical Values of t
Critical Values of
Critical Values of F
Critical Values of the Studentized Range
Critical Values for the Durbin-Watson Statistic
Critical Values for the Wilcoxon Rank Sum Test
Critical Values for the Wilcoxon Signed Rank Sum Test
Critical Values for the Spearman Rank Correlation Coefficient
Control Chart Constants
Answers to Selected Even-Numbered Exercises