Technometrics · 1991 · 164 citations · 2 references
Natural SciencesMathematicsProbability TheoryStatisticsStochastic ModelingConditional ProbabilityDiscrete ProbabilityProbabilistic ModelingProbability ConceptsProbability DistributionsRandom VariablesBivariate DistributionsContinuous Probability DistributionsContinuous Random VariablesDiscrete Probability DistributionsDiscrete Random VariablesMoment-generating FunctionsMultivariate DistributionsMultivariate Random Variables
The book offers a thorough introduction to probability, covering deterministic and probabilistic models, foundational concepts, discrete and continuous distributions, multivariate extensions, and key approximation theorems, with illustrative examples and exercises. It presents extended applications including Poisson processes, birth–death processes, queueing theory, renewal theory, and computational simulations. 1.
1. PROBABILITY AND THE WORLD AROUND US Why Study Probability / Deterministic and Probabilistic Models / Applications of Probability / A Brief Historical Note / A Look Ahead 2. PROBABILITY Understanding Randomness: An Intuitive Notion of Probability / A Brief Review of Set Notation / Definition of Probability / Counting Rules Useful in Probability / Conditional Probability and Independence / Rules of Probability / Odds, Odds Ratios, and Relative Risk / Activities for Students: Simulation / Summary / Supplementary Exercises 3. DISCRETE PROBABILITY DISTRIBUTIONS Random Variables and Their Probability Distributions / Expected Values of Random Variables / The Bernoulli Distributions / The Binomial Distribution / The Geometric Distribution / The Negative Binomial Distribution / The Poisson Distribution / The Hypergeometric Distribution / The Moment-generating Functions / The Probability-generating Function / Markov Chains / Activities for Students: Simulation / Summary / Supplementary Exercises 4. CONTINUOUS PROBABILITY DISTRIBUTIONS Continuous Random Variables and Their Probability Distributions / Expected Values of Continuous Random Variables / The Uniform Distribution / The Exponential Distribution / The Gamma Distribution / The Normal Distribution / The Beta Distribution / The Weibull Distribution / Reliability / Moment-generating Functions for Continuous Random Variables / Expectations of Discontinuous Functions and Mixed Probability Distributions / Activities for Students: Simulation / Summary / Supplementary Exercises 5. MULTIVARIATE PROBABILITY DISTRIBUTIONS Bivariate and Marginal Probability Distributions / Conditional Probability Distributions / Independent Random Variables / Expected Values of Functions of Random Variables / The Multinomial Distribution / More on the Moment-generating Function / Conditional Expectations / Compounding and its Applications / Summary / Supplementary Exercises 6. FUNCTIONS OF RANDOM VARIABLES Introduction / Method of Distribution Functions / Method of Transformations / Method of Conditioning / Method of Moment-generating Functions / Order Statistics / Probability-generating Functions: Applications to Random Sums of Random Variables / Summary / Supplementary Exercises 7. SOME APPROXIMATIONS TO PROBABILITY DISTRIBUTIONS: LIMIT THEOREMS Introduction / Convergence in Probability / Convergence in Distribution / The Central Limit Theorem / Combination of Convergence in Probability and Convergence in Distribution / Summary / Supplementary Exercises 8. EXTENDED APPLICATIONS OF PROBABILITY The Poisson Process / Birth and Death Processes: Biological Applications / Queues: Engineering Applications / Arrival Times for the Poisson Process / Infinite Server Queue / Renewal Theory: Reliability Applications / Summary / Exercises / APPENDIX TABLES / NOTES ON COMPUTER SIMULATIONS / REFERENCES / ANSWERS TO SELECTED EXERCISES / INDEX
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Introduction to Probability Theory.
H. C. Fryer, Paul G. Hoel, Sidney C. Port et al. · Journal of the American Statistical Association · 1972 · 808 citations