Probability and statistics for engineers / Richard L. Scheaffer, James T. McClave.

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