Spring 2011 Exam 2 Outline

Spring 2011 Exam 2 Outline - (4.3 Q Weibull Random...

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Probability and Statistics for Engineering Spring 2011 Exam 2 Outline Chapter 3. Discrete Distributions V. Discrete Poisson Distribution (definition, density, mean, variance, computing probabilities) (3.8) Chapter 4. Continuous Distributions A. Densities (4.1) B. Cumulative Distribution Function (4.1) C. Expected Value (4.2) D. Median E. Variance and Standard Deviation (4.2) F. Rules for Expected Value, Variance, and Standard Deviation (4.2) G. Chebyshev's Inequality H. Moment Generating Function (4.2) I. Normal Distribution (4.4) J. Normal Approximation to the Binomial Distribution (4.6) K Normal Probability Rule (4.5) L. Standard Normal Distribution (4.4) M. Gamma Function (4.3) N. Gamma Random Variable (4.3) O. Special Case: Exponential Random Variable (4.3) P. Application: Time to Occurrence of First Event — Continuous Poisson Distribution
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Unformatted text preview: (4.3) Q. Weibull Random Variable (4.7) R. Failure Density (4.7) S. Reliability Function (4.7) T. Hazard Rate (4.7) U. Reliability of Series Systems and Parallel Systems (4.7) Chapter 5. Joint Distributions A. Joint Densities (5.1) B. Marginal Densities (5.1) C. Independence of Random Variables (5.1) D. Expected Value (5.2) E. Covariance (5.2) F. Correlation (5.3) G. Theorems Involving Independence, Expectation,Variance, Covariance, and Correlation (5.2 and 5.3) H. Conditional Densities (5.4) I. Curves of Regression (5.4) Chapter 6. Descriptive Statistics A. Population vs. Sample (6.1) B. Bias, Random Sample (6.1) C. Parameter vs. Statistic (6.1) D. Sample Mean (6.3) E. Sample Median (6.3) F. Sample Variance and Standard Deviation (6.3) G. Sample Range (6.3)...
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