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Statistics for Business and Economics James T. McClave

Statistics for Business and Economics By James T. McClave

Statistics for Business and Economics by James T. McClave


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Summary

An introductory text in statistics for business and economics. This edition aims to prepare business student's to think critically about reported data and to use appropriate statistical method to make good decisions.

Statistics for Business and Economics Summary

Statistics for Business and Economics by James T. McClave

A comprehensive introduction to Business Statistics for students with a background in high school algebra. Extensively revised, the Seventh edition better prepares today's business students to think critically about reported data and to use appropriate statistical methods to make good decisions. Greater emphasis has been given to interpretation of computer output (Excel, Minitab, SPSS, SAS) over manual calculation. Six new, real cases make use of extensive data sets that are packaged with the book and a new Internet Lab feature connects students to the future. The supplements package has been extensively revised to include an Annotated Instructor's Manual, a PowerPoint Lecture tool, and a free Excel supplement for those seeking step-by-step instruction.

Table of Contents

Each chapter concludes with a Quick Review. 1. Statistics, Data, and Statistical Thinking. The Science of Statistics. Types of Statistical Applications in Business. Fundamental Elements of Statistics. Processes (Optional). Types of Data. STATISTICS IN ACTION: Quality Improvement: U.S. Firms Respond to the Challenge from Japan. Collecting Data. The Role of Statistics in Managerial Decision-Making. STATISTICS IN ACTION: A 20/20 View of Survey Results: Fact or Fiction. 2. Methods for Describing Sets of Data. Describing Qualitative Data. STATISTICS IN ACTION: Pareto Analysis. Graphical Methods for Describing Quantitative Data. The Time Series Plot (Optional). Summation Notation. Numerical Measures of Central Tendency. Numerical Measures of Variability. Interpreting the Standard Deviation. Numerical Measures of Relative Standing. Quartiles and Box Plots (Optional). Graphing Bivariate Relationships (Optional). Distorting the Truth with Descriptive Techniques. STATISTICS IN ACTION: Car and Driver's "Road Test Digest." Quick Review. SHOWCASE: The Kentucky Milk Case - Part I. INTERNET LAB: Accessing and Summarizing Business and Economics Data Maintained by the U.S. Government. 3. Probability. Events, Sample Spaces, and Probability. STATISTICS IN ACTION: Game Show Strategy: To Switch or Not to Switch. Unions and Intersections. Complementary Events. The Additive Rule and Mutually Exclusive Events. Conditional Probability. The Multiplicative Rule and Independent Events. Random Sampling. STATISTICS IN ACTION: Lottery Buster. 4. Discrete Random Variables. Two Types of Random Variables. Probability Distributions for Discrete Random Variables. Expected Values of Discrete Random Variables. STATISTICS IN ACTION: Portfolio Selection. The Space Shuttle Challenger: Catastrophe in Space. The Binomial Random Variable. The Poisson Random Variable (Optional). 5. Continuous Random Variables. Continuous Probability Distributions. The Uniform Distribution (Optional). The Normal Distribution. STATISTICS IN ACTION: IQ, Economic Mobility , and the Bell Curve Approximating a Binomial Distribution with a Normal Distribution. The Exponential Distribution (Optional). STATISTICS IN ACTION: Queuing Theory. 6. Sampling Distributions. The Concept of Sampling Distributions. Properties of Sampling Distributions: Unbiased and Minimum Variance. STATISTICS IN ACTION: Reducing Investment Risk Through Diversification. The Sampling Distribution of the Sample Mean. STATISTICS IN ACTION: The Insomnia Pill. Quick Review. SHOWCASE: The Furniture Fire Case. INTERNET LAB: Analyzing Monthly Business Start-ups. 7. Inferences Based on a Single Sample: Estimation with Confidence Intervals. Large-Sample Confidence Interval for a Population Mean. Small-Sample Confidence Interval for a Population Mean. STATISTICS IN ACTION: Scallops, Sampling, and the Law. Large-Sample Confidence Interval for a Population Proportion. Determining the Sample Size. STATISTICS IN ACTION: Is Caffeine Addictive? Finite Population Correction for Simple Random Sampling (Optional). Sample Survey Designs. STATISTICS IN ACTION: Sampling Error versus Nonsampling Error. 8. Inferences Based on a Single Sample: Tests of Hypothesis. The Elements of a Test of Hypothesis. STATISTICS IN ACTION: Statistics Is Murder! Large-Sample Test of Hypothesis About a Population Mean. STATISTICS IN ACTION: Statistical Quality Control, Part I. Observed Significance Levels: p-values. Small Sample Test of Hypothesis About a Population Mean. Large-Sample Test of Hypothesis About a Population Proportion. STATISTICS IN ACTION: Statistical Quality Control, Part II. Calculating Type II Error Probabilities. More about b (Optional). 9. Inferences Based an Two Samples: Confidence Intervals and Tests of Hypotheses. Comparing Two Population Means: Independent Sampling. STATISTICS IN ACTION: The Effect of Self-Managed Work Teams on Family Life. Comparing Two Population Means: Paired Difference Experiments. Comparing Two Population Proportions: Independent Sampling. Determining the Sample Size for Comparing Means and Proportions. STATISTICS IN ACTION: Unpaid Overtime and the Fair Labor Standards Act. Comparing Two Population Variances: Independent Sampling... SHOWCASE: The Kentucky Milk Case - Part II. INTERNET LAB: Choosing Between Economic Indicators. 10. Simple Linear Regression. Probabilistic Models. Fitting the Model: The Least Squares Approach. Model Assumptions. An Estimator of o^2. Assessing the Utility of the Model: Making Inferences about the Slope b1. The Coefficient of Correlation. STATISTICS IN ACTION: New Jersey Banks - Serving Minorities? The Coefficient of Determination. Using the Model for Estimation and Prediction. STATISTICS IN ACTION: Statistical Assessment of Damage to Bronx Bricks. Simple Linear Regression: An Example. 11. Multiple Regression. Multiple Regression: The Model and the Procedure. Fitting the Model: The Least Squares Approach. Model Assumptions. Inferences About the b Parameters. Checking the Usefulness of a Model: R^2 and the Analysis of Variance F-Test. Using the Model for Estimation and Prediction. Multiple Regression: An Example. Residual Analysis: Checking the Regression Assumptions. STATISTICS IN ACTION: Predicting the Price of Vintage Red Bordeaux Wine. Some Pitfalls: Estimability, Multicollinearity, and Extrapolation. STATISTICS IN ACTION: "Wringing" The Bell Curve. 12. Model Building. Introduction. The Two Types of Independent Variables: Quantitative and Qualitative. Models with a Single Quantitative Independent Variable. Models with Two or More Quantitative Independent Variables. Testing Portions of a Model. Models with One Qualitative Independent Variable. Comparing the Slopes of Two or More Lines. Comparing Two or More Response Curves. STATISTICS IN ACTION: Forecasting Peak Hour Traffic Volume. Stepwise Regression. Quick Review. SHOWCASE: The Cando Sales Case. INTERNET LAB: Using the Consumer Price Index in Business Forecasts of Labor, Wages, and Compensation. 13. Methods for Quality Improvement. Quality, Processes, and Systems. STATISTICS IN ACTION: Deming's 14 Points. Statistical Control. The Logic of Control Charts. A Control Chart for Monitoring the Mean of a Process: The x-Chart. A Control Chart for Monitoring the Variation of a Process: The R-Chart. A Control Chart for Monitoring the Proportion of Defectives Generated by a Process: The p-Chart. Diagnosing the Causes of Variation (Optional). STATISTICS IN ACTION: Quality Control in a Service Operation. Capability Analysis. 14. Time Series: Descriptive Analyses, Models, and Forecasting. Descriptive Analysis: Index Numbers. STATISTICS IN ACTION: The Consumer Price Index: CPI-U and CPI-W. Descriptive Analysis: Exponential Smoothing. Time Series Components. Forecasting: Exponential Smoothing. Forecasting Trends: The Holt-Winters Model (Optional). Measuring Forecast Accuracy: MAD and RMSE. Forecasting Trends: Simple Linear Regression. STATISTICS IN ACTION: Forecasting the Demand for Emergency Room Services. Seasonal Regression Models. Autocorrelation and the Durbin-Watston test. Quick Review. SHOWCASE: The Gasket Manufacturing Case. INTERNET LAB: Quality Management Outside of the Manufacturing Operation. 15. Design of Experiments and Analysis of Variance. Elements of a Designed Experiment. The Completely Randomized Design: Single Factor. Multiple Comparisons of Means. STATISTICS IN ACTION: Is Therapy the New "Diet Pill" for Binge Eaters? Factorial Experiments. STATISTICS IN ACTION: Improving a Ground Meat Canning Process Through Experimental Design. Using Regression for ANOVA (Optional). 16. Nonparametric Statistics. Introduction. Single Population Inferences: The Sign Test. Comparing Two Populations: The Wilcoxon Rank Sum Test for Independent Samples. Comparing Two Populations: The Wilcoxon Signed Rank Test for the Paired Difference Experiment. STATISTICS IN ACTION: Reanalyzing the Scallop Weight Data. The Kruskal-Wallis H-Test for a Completely Randomized Design. STATISTICS IN ACTION: Taxpayers versus the IRS: Selecting the Trial Court. Spearman's Rank Correlation Coefficient. 17. The Chi-Square Test and the Analysis of Contingency Tables. One-Dimensional Count Data: The Multinomial Distribution. Contingency Tables. STATISTICS IN ACTION: Ethics in Computer Technology and Use. A Word of Caution About Chi-Square Tests. SHOWCASE: Discrimination in the Workplace. INTERNET LAB: Sampling and Analyzing NYSE Stock Quotes. 18. Decision Analysis. Introduction. Three Types of Decision Problems. Decision-Making Under Uncertainty. Basic Concepts. Two Ways of Expressing Outcomes: Payoffs and Opportunity Losses. Characterizing the Uncertainty in Decision-Problems. Solving the Decision Problem Using the Expected Payoff Criterion. STATISTICS IN ACTION: Evaluating Uncertainty in Research and Development. The Expected Utility Criterion. Classifying Decision-Makers by Their Utility Functions. Revising State of Nature Probabilities: Bayes' Rule. Solving Decision Problems Using Posterior Probalilitics. The Expected Value of Sample Information: Preposterior Analysis. STATISTICS IN ACTION: Hurricanes: To Seed or Not to Seed? Appendix A: Basic Counting Rules. Appendix B: Tables. Appendix C: Calculation Formulas for Analysis of Variance. Answers to Selected Exercises. References. Index.

Additional information

GOR002301207
9780138402327
0138402329
Statistics for Business and Economics by James T. McClave
Used - Very Good
Hardback
Pearson Education (US)
1997-12-10
1067
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in very good condition, but if you are not entirely satisfied please get in touch with us

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