Probability and statistics in the engineering and computing sciences /
J.S. Milton, Jesse C. Arnold.
- Singapore ; Boston ; New york : McGraw-Hill, c2003, 1995, 1990, 1986.
- xv, 431 p. : ill (some col). ; 26 cm.
CONTENT
Chapter 1 : Introduction to probability and counting 1.1 Interpreting probabilities 1.2. Sample spaces and events Chapter summary pg 8 Exercises pg 9
Chapter 2 : Some probability laws 2.1 Axioms of probability 2.2 Conditional probability 2.3 Independence and the multiplication rule 2.4 Bayes' theorem Chapter summary pg 24 Exercises pg 25
Chapter 3 : Discrete distributions 3.1 Random Variables 3.2 Discrete probability denstities 3.3 Expectation and distribution parameters 3.4 Binomial distribution Chapter summary pg49 Exercises pg 50 Review Exercises pg 58
Chapter 4 : Continuous distribution 4.1 Continuous distribution 4.2 Expectation and distribution parameters 4.3 Normal distribution etc Chapter summary pg 77 Exercises pg 78
Chapter 5 : Descriptive statistics 5.1 Random sampling 5.2 Picturing the distribution 5.3 Sample statistics Chapter summary pg 109 Exercises pg116
Chapter 6 : Estimation 6.1 Point estimation 6.2 Functions of Random variables- distribution of x 6.3 Interval estimation and the central limit theorem Chapter summary pg 129 Exercises pg130
Chapter 7 : Inferences on the mean and variance of a distribution 7.1 Interval estimation of variability 7.2 Estimating the mean and the student-t distribution 7.3 Hypothesis testing etc Chapter summary pg 163 Exercise pg 164
Chapter 8 : Inferences on proportion 8.1 Estimating proportion 8.2 Testing hypothesis on a proportion 8.3 Comparing two proportion : estimation 8.4 Comparing two proportion : hypothesis testing Chapter summary pg197 Exercises 198
Chapter 9 : Comparing two mean and two variance 9.1 .Point estimation : Independent samples 9.2 Comparing variances: the f distributing 9.3 Comparing mean : variances equal (pooled test) etc Chapter summary pg227 Exercises 228
Chapter 10 : Simple linear regression and correlation 10. Model and parameter estimation 10.2 Properties of least squares estimation 10.3 Confidence interval estimation and hypothesis testing etc Chapter Summary 285 Exercises 286
Chapter 11 : Analysis of variance 11.1 One way classification fixed effect model 11.2 Comparing variance 11.3 Pairwise comparisions etc Chapter summary p317 Exercises 318
Chapter 12 : Categorical data 12.1 Multinomial distribution 12.2 Chi-Squared goodness of fit test 12.3 Testing for independence 12.4 Comparing proportion Chapter summary pg 342 Exercises 343
Index : p. 422-431
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Engineering mathematics. Electronic data processing. Probabilities. Statistics.