Applied Statistics

Name: Applied Statistics
Price: 7.29 USD
Availability: InStock
ISBN: 9780534371128

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…

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?



Introduction



Key Statistical Concepts



Statistics and the Computer



World Wide Web and Learning Center



Introduction to Microsoft Excel



Graphical Descriptive Techniques



Introduction



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



Summary



Numerical Descriptive Techniques for Interval Data



Introduction



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



Summary



Probability



Introduction



Assigning Probability to Events



Joint, Marginal, and Conditional Probability



Probability Rules and Trees



Summary



Let's Make a Deal



To Bunt or Not to Bunt, That Is the Question



Random Variables and Discrete Probability Distributions



Introduction



Random Variables and Probability Distributions



Describing the Population/Probability Distribution



Binomial Distribution



Poisson Distribution



Summary



To Bunt or Not to Bunt, That Is the Question, Part II



Continuous Probability Distributions



Introduction



Probability Density Functions



Normal Distribution



Other Continuous Distributions



Summary



Sampling and Sampling Plans



Introduction



Sampling



Sampling Plans



Errors Involved in Sampling



Summary



Sampling Distributions



Introduction



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



Summary



Introduction to Estimation



Introduction



Concepts of Estimation



Estimating the Population Mean when the Population Standard Deviation Is Known



Selecting the Sample Size



Simulation Experiments (Optional)



Summary



Introduction to Hypothesis Testing



Introduction



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



Summary



Inference About A Single Population



Introduction



Inference about a Population Mean when the Standard Deviation Is Unknown



Inference about a Population Variance



Inference about a Population Proportion



Summary



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



Introduction



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



Summary



Bonanza International



Accounting Course Exemptions



Statistical Inference: Review of Chapters 11 and 12



Introduction



Guide to Identifying the Correct Technique: Chapters 11 and 12



Quebec Separation: Oui ou non?



Host Selling and Announcer Commercials



Analysis of Variance



Introduction



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



Summary



Chi-Squared Tests



Introduction



Chi-Squared Goodness-of-Fit Test



Chi-Squared Test of a Contingency Table



Summary of Tests on Nominal Data



Chi-Squared Test for Normality



Summary



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



Introduction



Wilcoxon Rank Sum Test



Sign Test and Wilcoxon Signed Rank Sum Test



Kruskal-Wallis Test



Friedman Test



Summary



Simple Linear Regression and Correlation



Introduction



Model



Estimating the Coefficients



Error Variable: Required Conditions



Assessing the Model



Using the Regression Equation



Coefficients of Correlation



Regression Diagnostics I



Summary



Predicting University Grades from High School Grades



Insurance Compensation for Lost Revenues



Multiple Regression



Introduction



Model and Required Conditions



Estimating the Coefficients and Assessing the Model



Regression Diagnostics II



Regression Diagnostics III (Time Series)



Nominal Independent Variables



Summary



Quebec Referendum Vote: Was There Electoral Fraud?



Quebec Referendum Vote: The Rebuttal



Statistical Inference: Conclusion



Introduction



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



Tables



Answers to Selected Even-Numbered Exercises


Index