Andere Kunden interessierten sich auch für
![Quantum Stochastic Calculus with Unbounded Coefficient]( "Quantum Stochastic Calculus with Unbounded Coefficient")
Quantum Stochastic Calculus with Unbounded Coefficient32,99 €![Probability Limits of X-Bar Chart for Non-normal Distribution]( "Probability Limits of X-Bar Chart for Non-normal Distribution")
Probability Limits of X-Bar Chart for Non-normal Distribution53,99 €![TESTING THE EQUALITY OF COEFFICIENTS OF VARIATION AND COMPARISONS]( "TESTING THE EQUALITY OF COEFFICIENTS OF VARIATION AND COMPARISONS")
TESTING THE EQUALITY OF COEFFICIENTS OF VARIATION AND COMPARISONS32,99 €![The C-S method in computation of the logistic normal integral]( "The C-S method in computation of the logistic normal integral")
The C-S method in computation of the logistic normal integral26,99 €![Skew-Normal Distribution with a Cauchy Skewing Function]( "Skew-Normal Distribution with a Cauchy Skewing Function")
Skew-Normal Distribution with a Cauchy Skewing Function25,99 €![Bayesian Multiple Hypothesis Testing for Normal Distribution]( "Bayesian Multiple Hypothesis Testing for Normal Distribution")
Bayesian Multiple Hypothesis Testing for Normal Distribution38,99 €
Many of the phenomena observed in biological, physical and other natural sciences follow normal distribution. In the past few years, the primary interest was the inference concerning mean and variance of the observations, especially those which were related to the biological measurements. In such experimental study the past data provides information on the coefficient of variation (c.v.). When the data is analyzed for the final trials, past information on the variability in the yield can be made use of, for the estimation of the mean. The c.v. is a stable measure of dispersion and thus does not change quite rapidly over the years or between the locations. The focus of this book is the inference concerning normal mean with known c.v. The performance of the estimators proposed in the literature are extensively studied and new tests are proposed for the mean. The performances of the tests are studied through simulations and through higher order asymptotics by deriving Edgeworth expansion for the null distribution of the test statistics.