03433nam a2200157   4500020001500000050001600015100002400031245010300055250001300158260004000171300002600211440005200237500001600289505295400305650001603259  a0704228646  aQA276b.M77  aMood, Alexander M.   aIntroduction to the theory of statistics cAlexander M. Mood, Franklin A Graybill & Duane C. Boes   a3rd ed.   aNew York bMcGraw-Hill, Inc. c1974  axvi, 564p. : c24cm.   aMcGraw-Hill Series in Probability and Satistics  aStatistics   aPart 1. Probability 
Chapter 1. Introduction and Summary 
Chapter 2. Kinds of Probability 
Chapter 3. Probability -Axiomatic 

Part II Random Variables, Distributions Functions, and Expectation
Chapter 1. Introduction and Summary
Chapter 2. Random Variable and Cummulative Distribution Function
Chapter 3. Destiny Functions 
Chapter 4. Expectations and Moments 

Part III Special Parametric Families of Universities Distributions 
Chapter 1. Introduction and Summary 
Chapter 2. Discrete Distribution 
Chapter 3. Continuous Distribution 
Chapter 4. Comments

Part IV Joint and Conditional Distributions, Stochastic Independence, More Expectation
Chapter 1. Introduction and Summary
Chapter 2. Joint Distribution Functions 
Chapter 3. Conditional Distribution and Stochastic Independence 
Chapter 4. Expectation 
Chapter 5. Bivariate Normal Distribution 

Part V Distribution of Functions of Random Variables
Chapter 1. Introduction and Summary 
Chapter 2. Expectations of Functions of Random Variables 
Chapter 3. Cumulative-distributions of Functions of Random Variables 
Chapter 4. Moment-generating-function Technique 
Chapter 5. The Transformation Y=g (X)
Chapter 6. Transformation 

Part VI. Sampling and Sampling Distributions 
Chapter 1. Introduction and Summary 
Chapter 2. Sampling 
Chapter 3. Sample Mean 
Chapter 4. Sampling from the Normal Distributions

Part VII Parametric Point Estimation 
Chapter 1. Introduction and Summary 
Chapter 2. Methods of Finding Estimates
Chapter 3. Properties of Point Estimation 
Chapter 4. Sufficiency
Chapter 5. Unbiased Estimation 
Chapter 6. Location or Scale Invariance 
Chapter 7. Bayes Estimators 
Chapter 8. Vector of Parameters 
Chapter 9. Optimum Properties of Maximum-likelihood Estimation 

VIII Parametric Interval Estimation 
Chapter 1. Introduction and Summary 
Chapter 2. Confidence Intervals 
Chapter 3. Sampling from the Normal Distribution 
 Chapter 4. Methods of finding Confidence Intervals 
Chapter 5. Large-Sample Confidence Interval
Chapter 6. Bayesian Interval Estimates 

Part IX Test of Hypotheses
Chapter 1. Introduction and Summary 
Chapter 2. Simple Hypothesis versus Simple Alternative 
Chapter 3. Composite Hypotheses 
Chapter 4. Tests of Hypotheses - Sampling from the Normal Distribution 
Chapter 5. Chi-Square Test
Chapter 6. Tests of Hypotheses - Sampling from the Normal Distribution 
Chapter 7. Sequential Test of Hypotheses 

Part X Linear Models 
Chapter 1. Introduction and Summary 
Chapter 2. Examples of the Linear Model 
Chapter 3. Definition of Linear Model 
Chapter 4. Point Estimation - Case A
Chapter 5. Confidence Intervals - Case A 
Chapter 6. Test of Hypotheses - Case A
Chapter 7. Point Estimation 

Part XI Nonparametric Methods 
Chapter 1. Introduction and Summary 
Chapter 2. Inferences Concerning a Cumulative Distribution Function 
Chapter 3. Inferences Concerning Qualities 
Chapter 4. Tolerance limits
Chapter 5. Equality of Two Distribution 

   aStatistics