Introduction to Probability and Statistics for Engineers and ScientistsReviews fundamental concepts and applications of probability and statistics. After a general overview, it considers special types of random variables, using examples which illustrate their wide variety of applications. Also examines their calculation and presents computer programs that calculate the probability distribution, and the inverses of binomial, poisson, normal, t, F, and Chi-square distributions. Coverage includes such topics as the sample mean, sample variance, sample median, as well as histograms, empirical distribution functions, and stem-and-leaf plots. A program for computing sample mean and sample variance for a given data set is included. A diskette of 35 programs for the IBM PC is available, giving exact answers or approximations where appropriate. |
Contents
CHAPTER | 1 |
Sample Space and Events | 2 |
Venn Diagrams and the Algebra of Events | 4 |
Copyright | |
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20 PRINT ENTER 95 percent confidence approximately binomial random variable chi-square distribution chi-square random variable COMPUTES THE VALUE confidence interval control chart control limits data values degrees of freedom denote the number determine distributed with mean distribution function ENTER THE NUMBER equal Equation event Example exponential distribution F-STATISTIC following data foregoing function F given GOTO H₁ Hence least squares estimators level of significance maximum likelihood estimator normal population normal random variable normally distributed null hypothesis number of defects obtain outcome p-value P₁ percent confidence interval Poisson distribution Poisson random variable possible values PRINT THIS PROGRAM probability density function probability mass function Problem PROGRAM COMPUTES random numbers regression reject result run Program sample mean sample variance significance level simulation standard deviation sum of squares Suppose test statistic Test the hypothesis variable with parameters variance o² X₁ X₂ Y₁ μο Σ Σ