TY - BOOK AU - Scheaffer,Richard L. AU - McClave,James T. TI - Probability and statistics for engineers SN - 0534209645 U1 - 519.202462 20 PY - 1995/// CY - Belmont, California. PB - Duxbury Press KW - Statistics KW - Probabilities N1 - CONTENT 1 Data and Decisions 1.1 Quality Really is Job One 1.2 A Model for problem Solving 1.3 A real Application of the problem- Solving Model 1.4 Basic Tools fro Analysing Data 1.5 Refinements of the Data Analysis Tools etc 2 From Data Tables to Discrete Probability 2.1 Understanding Randomness: An Intuitive Notion of Probability 2.2 Using Randomness : How to Obtain Good Data 2.3 Table and Sets 2.4 Definition of Probability 2.5 Counting Rules Useful in Probability etc 3 Discrete Probability Distributions 3.1 Random Variables and Their Probability Distributions 3.2 Expected Values of random variables 3.3 The Bernoulli Distribution 3.4 The Binomial Distribution 3.5 The Geometric Distribution etc 4 Continuous Probability Distributions 4.1 Continuous Random Variables and their Probability Distributions 4.2 Expected values of continuous Random Variables 4.3 The Uniform Distribution 4.4 The exponential Distribution 4.5 The Gamma Distribution etc 5 Multivariate Probability Distributions 5.1 Bivariate and Marginal Probability Distributions 5.2 Conditional Probability Distribution 5.3 Independent Random Variables 5.4 Expected Values of Functions of Random Variables 5.5 The Multinomial Distribution etc 6. Statistics, SamplingDistribution, and Control Charts 6.1 Introduction 6.2 The Sample Mean and Variance 6.3 The Sampling Distribution of x 6.4 The normal Approximation to the Binomial Distribution 6.5 The Sampling Distribution etc 7 Estimation 7.1 Introduction 7.2 Properties of point Estimators 7.3 Confidence Intervals: The single - Sample Case 7.4 Confidence Intervals: The Multiple- Sample Case 7.5 Prediction Intervals etc 8 Hypothesis Testing 8.1 Introduction 8.2 Hypothesis Testing: The single -Sample Case 8.3 Hypothesis Testing: The Multiple Sample case 8.4 Tests on frequency Data 8.5 Goodness- of Fit Tests etc 9 Simple Regression 9.1 Introduction 9.2 Probabilistic Models 9.3 Fitting the Model: The Least Squares Approach 9.4 The Probability Distribution of the Random Error Component 9.5 Assessing the Adequacy of the Model: Making inferences about Slope etc 10 Multiple Regression Analysis 10.1 Introduction 10.2 Fitting the Model: The Least-squares Approach 10.3 Estimation of the Variance 10.4 A Test of Model Adequacy : The Coefficient of Determination 10.5 Estimating and Testing Hypotheses about Individuals etc 11 Design of experiments and the Analysis of Variance 11.1 Introduction to design Experiments 11.2 Analysis of Variance for the Completely Randomized Design 11.3 A Linear Model fro the Completely Randomized Design 11.4 Estimation for the Completely Randomized design 11.5 Analysis of Variance for the Randomzed Block Design ; Index : p. 740 - 745 ER -