Introduction to Probability　1.1 INTRODUCTION:WHY STUDY PROBABILITY?　1.2 THE DIFFERENT KINDS OF PROBABILITY　　A. Probability as Intuition　　B. Probability as the Ratio of Favorable to Total Outcomes (Classical Theory)　　C. Probability as a Measure of Frequency of Occurrence　　D. Probability Based on an Axiomatic Theory　1.3 MISUSES,MISCALCULATIONS,AND PARADOXES 1N　PROBABILITY　1.4 SETS,FIELDS,AND EVENTS　Examples of Sample Spaces　1.5 AXIOMATIC DEFINITION OF PROBABILITY　1.6 JOINT, CONDITIONAL,AND TOTAL PROBABILITIES;INDEPENDENCE　1.7 BAYES' THEOREM AND APPLICATIONS　1.8 COMBINATORICS　　Occupancy Problems　　Extensions and Applications　1.9 BERNOULLI TRIALS--BINOMIAL AND MULTINOMIAL　　PROBABILITY LAWS　　Multinomial Probability Law　1.10 ASYMPTOTIC BEHAVIOR oF THE BINOMIAL LAW： THE POISSON LAW　1.11 NORMAL APPROXIMATION TO THE BINOMIAL LAW　1.12 SUMMARY PROBLEMS REFERENCES2　Random Variables 2.1 INTRODUCTION 2.2 DEFINITION OF A RANDOM VARIABLE 2.3 PROBABILITY DISTRIBUTION FUNCTION 2.4 PROBABILITY DENSITY FUNCTION(pdf) Four Other Common Density Functions More Advanced Density Functions 2.5 CONTINUOUS,DISCRETE,AND MIXED RANDOM VARIABLES　 Examples of Probability Mass Functions　2.6 CONDITIONAL AND JOINT DISTRIBUTIONS AND　　DENSITIES 2.7 FAILURE RATES 2.8 FUNCTIONS OF A RANDOM VARIABLE 2.9 SOLVING PROBLEMS OF THE TYPE 2.10 SOLVING PROBLEMS OF THE TYPE 2.11 SOLVING PROBLEMS OF THE TYPE W=h(X,Y) 2.12 SUMMARY PROBLEMS REFERENCES ADDITIONAL READING3. Expectation and Introduction to Estimation 3.1 EXPECTED VALUE OF A RANDOM VARIABLE On the Validity of Equation 3.1 -8　3.2 CONDITIONAL EXPECTATIONS　　Conditional Expectation as a Random Variable……