Introduction To Probability And Statistics For Science, Engineering, And Finance

摘要: Data Analysis Orientation The Role and Scope of Statistics in Science Engineering Types Data: Examples from Engineering, Public Health, Finance Frequency Distribution a Variable Defined on Population Quantiles Measures Location (Central Value) Variability Covariance, Correlation, Regression: Computing Stock's Beta Mathematical Details Derivations Large Sets Probability Theory Sample Space, Events, Axioms Models Random Sampling Conditional Bayes' Theorem Binomial Discrete Variables Their Functions Expected Value Variance Hypergeometric Poisson Moment Generating Function: Continuous with Functions: Definition Value, Moments, Normal Distribution: Basic Properties Lognormal A Model for the Stock Prices Approximation to Other Important Distributions Multivariate Joint Multinomial Mean Sum Why Have An Application Central Limit Modern Portfolio Risk Free Risky Investing Single Multi-Period Options Black-Scholes Formula Process Applications Bernoulli Reliability Point Interval Estimation Estimating Parameters: Methods Confidence Intervals Difference Two Means Proportion Some Hypothesis Testing Tests Statistical Hypotheses: Concepts Comparing Populations Plots Concerning Parameter p Categorical Chi Square Contingency Tables Linear Regression Correlation Method Least Squares Simple Checking Multiple Matrix Approach Single-Factor Experiments: Factor ANOVA Treatment Contrasts Effects Design Multi-Factor Experiments Randomized Complete Block Designs Two-Factor n > 1 Observations per Cell 2k Factorial Quality Control x R Charts charts c Appendix: Answers Selected Odd-Numbered Problems Index Chapter Summary, Problems, To Probe Further sections appear at end each chapter.