Statistics for Applied Problem Solving and Decision Making
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Statistics for Applied Problem Solving and Decision Making

Statistics for Applied Problem Solving and Decision Making


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About the Book

Intended for the applied calculus-based, introductory statistics course for business and economics undergraduates and MBAs, this book presents business statistics as a problem-solving process, rather than as a means to achieve a numerical solution. Applied, data-driven, and copmuter-oriented, it emphasizes the principles of statistics as a foundation for application of statistical methodologies and real-life problems. Curve fitting and regression are introduced early, allowing students to use the computer from the start of the course. Statistical and spreadsheet software help students make the connections between probability models and actual data. The authors include sparing and careful use of calculus at critical points where a simple calculus reference or computation can totally eliminate the perplexing arbitrariness that is seen in 'cookbook' approaches.

Table of Contents:
PREFACE 1. INTRODUCTION Introduction / The Tools of Statistics / A Brief Course Outline 2. STATISTICAL RELATIONSHIPS: A FIRST LOOK Introduction / Fitting the Model y = b0 + b1x / The Sample Correlation Coefficient / Fitting Curvilinear Relationships / Summary 3. SAMPLES AND SAMPLE VARIATION Introduction / Methods of Sampling / Summarizing a Sample / Measuring Location and Dispersion (An Introduction) / Summary 4. PROBABILITY MODELS: AN INTRODUCTION Introduction / Discrete Probability Models / Continuous Probability Models / Summary 5. THE NORMAL CURVE Introduction / The Standard Normal Curve / The Z Transformation / The Central Limit Theorem / Summary / Normal Plots 6. THE BINOMIAL DISTRIBUTION Introduction / The Binomial Model / Using Normal Curves to Approximate Binomial Probabilities / Summary 7. THE HYPERGEOMETRIC, POISSON, AND EXPONENTIAL DISTRIBUTIONS Introduction / The Hypergeometric Distribution / The Poisson and Exponential Distributions / Summary / Proof of Theorem 7.3.4 8. MEANS AND STANDARD DEVIATIONS Introduction / Expected Value / The Population Standard Deviation / Summary / A Proof of Chebyshev?s Inequality (Theorem 8.3.1) 9. ESTIMATING PARAMETERS Introduction / The Method of Maximum Likelihood / Estimators / Margin of Error and Sample Size Determination / Summary 10. PRINCIPLES OF INFERENCE Introduction / Testing Hypotheses About u (Normal Data) / Confidence Intervals for u / Drawing Inferences About o2 / Binomial Data: Inferences About p / Poisson Data: Inferences About l / Summary 11. SOME COMMON TYPES OF DATA Introduction / Seven Common Experimental Designs / Summary 12. COMPARING MEANS Introduction / The Two-sample t Test / Testing H0: u1 = u2 = / / / = uk: The One-Way Analysis of Variance / The Paired t Test / Analyzing Randomized Block Data / Summary 13. STATISTICAL RELATIONSHIPS: A SECOND LOOK Introduction / The Simple Linear Model / Analyzing Categorical Data: The X2 Test for Independence / Summary 14. MULTIPLE REGRESSION Introduction / Least Squares Estimation / Hypothesis Testing / Model Building / Prediction Intervals and Influential Observations / Summary 15. TIME SERIES AND INDEX NUMBERS Introduction / Fitting a Time Series Model / Smoothing a Time Series / Simple and Composite Indexes / Weighted Composite Index Numbers / Summary 16. QUALITY CONTROL Introduction / X-charts / R-charts and S-charts / Other Control Charts / Specification Limits Versus Control Limits / Acceptance Sampling / Summary / APPENDIX A TABLES / BIBLIOGRAPHY / ANSWERS TO ODD-NUMBERED EXERCISES / INDEX


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Product Details
  • ISBN-13: 9780534930844
  • Publisher: Cengage Learning, Inc
  • Publisher Imprint: Brooks/Cole
  • Height: 236 mm
  • Returnable: N
  • Weight: 1270 gr
  • ISBN-10: 0534930840
  • Publisher Date: 10 Mar 1997
  • Binding: Hardback
  • Language: English
  • Spine Width: 23 mm
  • Width: 180 mm


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