Applied Statistics

ISBN-10: 0534371124

ISBN-13: 9780534371128

Edition: 2001

Authors: Gerald Keller

List price: $158.95
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Gerald Keller's new APPLIED STATISTICS WITH MICROSOFT EXCEL integrates Excel into the general introductory statistics course. Keller, the co-author of the market-leading STATISTICS FOR MANAGEMENT AND ECONOMICS, Fifth Edition, incorporates his proven three-step problem-solving process throughout this book. The first step, "Identify," is the work a statistician does before the calculations are performed, which entails organizing the experiment, gathering the data, and deciding which statistical techniques to employ. The second step, "Compute," is the computation with Excel. In this step, Keller shows the manual calculation for the simplest of techniques only. For example, he describes how to calculate the sample mean, variance, and standard deviation, how to compute the z-interval estimate of, and the z-test of. The third step, "Interpret," is the interpretation of the computer output, which requires an understanding of statistical concepts.
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Book details

List price: $158.95
Copyright year: 2001
Publisher: Brooks/Cole
Publication date: 12/21/2000
Binding: Hardcover
Pages: 784
Size: 8.50" wide x 9.50" long x 1.25" tall
Weight: 2.992
Language: English

Dr. Gerald Keller is Professor of Business at Wilfrid Laurier University, where he has taught statistics, management science, and operations management since 1974. He also has taught at the University of Toronto, the University of Miami, McMaster University, the University of Windsor, and the Beijing Institute of Science and Technology. Dr. Keller has consulted with banks on credit scoring and credit card fraud and has conducted market surveys for the Canadian government on energy conservation. The author of APPLIED STATISTICS WITH MICROSOFT EXCEL, Dr. Keller has also been published in OMEGA, IIE TRANSACTIONS, DECISION SCIENCES, INFOR, ECONOMICS LETTERS, and ARCHIVES OF SURGERY.

What is Statistics?
Key Statistical Concepts
Statistics and the Computer
World Wide Web and Learning Center
Introduction to Microsoft Excel
Graphical Descriptive Techniques
Types of Data
Graphically Describing Interval Data: Frequency Distributions and Histograms
Graphically Describing Nominal Data: Bar and Pie Charts
Describing Time-Series Data: Line Charts
Describing the Relationship between Two Interval Variables: Scatter Diagrams
Numerical Descriptive Techniques for Interval Data
Measures of Central Location
Measures of Variability
Other Measures of Shape (Optional)
Measures of Relative Standing and Box Plots
Measures of Linear Relationship
General Guidelines for Exploring Data
Assigning Probability to Events
Joint, Marginal, and Conditional Probability
Probability Rules and Trees
Let's Make a Deal
To Bunt or Not to Bunt, That Is the Question
Random Variables and Discrete Probability Distributions
Random Variables and Probability Distributions
Describing the Population/Probability Distribution
Binomial Distribution
Poisson Distribution
To Bunt or Not to Bunt, That Is the Question, Part II
Continuous Probability Distributions
Probability Density Functions
Normal Distribution
Other Continuous Distributions
Sampling and Sampling Plans
Sampling Plans
Errors Involved in Sampling
Sampling Distributions
Sampling Distribution of the Mean
Creating the Sampling Distribution by Computer Simulation (Optional)
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
Simulation Experiments (Optional)
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 A Single Population
Inference about a Population Mean when the Standard Deviation Is Unknown
Inference about a Population Variance
Inference about a Population Proportion
Pepsi's Exclusivity Agreement with a University
Pepsi's Exclusivity Agreement with a University: The Coke Side of the Equation
Number of Uninsured Motorists
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
Bonanza International
Accounting Course Exemptions
Statistical Inference: Review of Chapters 11 and 12
Guide to Identifying the Correct Technique: Chapters 11 and 12
Quebec Separation: Oui ou non?
Host Selling and Announcer Commercials
Analysis of Variance
Single-Factor (One-Way) Analysis of Variance: Independent Samples
Analysis of Variance Experimental Designs
Single-Factor Analysis of Variance: Randomized Blocks
Two-Factor Analysis of Variance: Independent Samples
Multiple Comparisons
Bartlett's Test
Chi-Squared Tests
Chi-Squared Goodness-of-Fit Test
Chi-Squared Test of a Contingency Table
Summary of Tests on Nominal Data
Chi-Squared Test for Normality
Predicting the Outcomes of Basketball, Baseball, Football, and Hockey Games from Intermediate Results
Can Exposure to a Code of Professional Ethics Help Make Managers More Ethical?
Nonparametric Statistical Techniques
Wilcoxon Rank Sum Test
Sign Test and Wilcoxon Signed Rank Sum Test
Kruskal-Wallis Test
Friedman Test
Simple Linear Regression and Correlation
Estimating the Coefficients
Error Variable: Required Conditions
Assessing the Model
Using the Regression Equation
Coefficients of Correlation
Regression Diagnostics I
Predicting University Grades from High School Grades
Insurance Compensation for Lost Revenues
Multiple Regression
Model and Required Conditions
Estimating the Coefficients and Assessing the Model
Regression Diagnostics II
Regression Diagnostics III (Time Series)
Nominal Independent Variables
Quebec Referendum Vote: Was There Electoral Fraud?
Quebec Referendum Vote: The Rebuttal
Statistical Inference: Conclusion
Identifying the Correct Technique: Summary of Statistical Inference
Do Banks Discriminate against Women Business Owners? I
Do Banks Discriminate against Women Business Owners? II
The Last Word
Ambulance and Fire Department Response Interval Study
PC Magazine Survey
WLU Graduate Survey
Evaluation of a New Antidepressant Drug
Nutrition Education Programs
Do Banks Discriminate against Women Business Owners? III
Sample Statistics from Data Files in Chapters 9 and 10
Answers to Selected Even-Numbered Exercises
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