No description available.

The testing of statistical hypotheses concerning two populations consists in determining the relationship between the cumulative distribution functions on the basis of random samples from each population. In the non-parametric case the only assumption made regarding the populations is that the two c.d.f's. are continuous. Thus the distribution of any statistic proposed to test the two samples must be independent of the functional form of the c.d.f.’s. One method of approach is based on the order relations of the sample values. A survey is made of such tests recently proposed and a new test is suggested based on sampling without replacement from a population of the positive integers 1, 2, 3, ... N . / Science, Faculty of / Mathematics, Department of / Graduate

Thesis (Ph. D.)--University of Wisconsin--Madison, 1984. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 143-146).

Thesis (Ph. D.)--Columbia University, 1939. / Vita. Bibliography: p. 55.

Thesis (Ph. D.)--University of Michigan, 1935. / Thesis note on p. 62. "Reprinted from the Annals of mathematical statistics, vol. VII, no. 2, June, 1936."

Acceptance sampling procedures are widely used in industry as part of the total quality control activities. The acceptance procedure is usually constructed based on a set of statistical and/or economic requirements specified by the producer and/or the consumer. After the acceptance procedure is determined, the users are interested in evaluating its statistical and economic characteristics. This dissertation presents a comprehensive approach for constructing and evaluating acceptance sampling procedures. A large variety of statistical and economic characteristics is studied, from both the producer's and consumer's viewpoints. A part of the acceptance procedure is the sampling plan. Various statistical characteristics of the sampling plan are studied. The statistical evaluation of the acceptance procedure consists of analyzing these characteristics. The economic analysis includes identification of the possible actions during the acceptance procedure and evaluation of the producer's profit and the consumer's cost functions associated with each action. Guidelines for applying the statistical and economic characteristics in the evaluation process are presented. In a real situation, sampling may be subjected to inspection errors, which can affect the statistical and economic characteristics of the acceptance procedure; so all the characteristics were restudied for an error-prone sampling inspection. The statistical and economic characteristics are used to specify sets of requirements for constructing acceptance procedures. Selection of an appropriate set is based on the needs of the user, the available data, and the conditions under which the procedure is to be applied. The concluding step is to combine the construction and evaluation methods into an overall analysis cycle of "construct-evaluate-reconstruct." Computer programs are given to facilitate application of the evaluation and construction processes. This study deals explicitly with single sampling plans for attributes. The analysis is based on the Bayesian approach in which the prior distribution is a mixed binomial with a beta weight function. However, the presented approach can be applied to any type of sampling and prior distribution. The results of the study can be used by decision makers as a tool to improve the use of acceptance procedures in a large variety of scenarios.

No description available.

We investigated the effect of different probability sampling designs (simple random sampling, stratified, cluster and systematic sampling designs) on estimates of age, gender proportions, and proportions of the population with different education levels, and access to water. To investigate the effect of the sample designs we used as a sampling frame the census 1994 data obtained from Central Statistical Agency of Ethiopia (CSA). In order to compare results obtained from different sampling designs, estimates of population means and proportions for selected variables at household levels using 1, 5 and 10% sample size is considered. The performance of these sampling techniques is observed on the following dimensions: relative accuracy, standard error, confidence intervals, precision and also we compared the effect of the different methods of calculating variances like Taylor series and jack-knife, the comparison of this two methods is done by drawing 100 different samples of 1% for stratified and cluster sampling. It was found that in general the relative accuracy for the selected variable obtained from the stratified sampling design is better than other estimates. We also find evidence that the 95% confidence interval constructed for each method contains the true population value, but the confidence interval for cluster sample is wider than the others that indicate less precision than others. The result of the comparison of the different methods of estimating the variance from the simulated population variance indicates that, for cluster sampling, both of the Taylor linearization and jack-knife methods tend to overestimate the population variance, whereas for stratified sampling the population standard error is in between of the standard error of the both methods indicating when one underestimates the other overestimates. Design effects were also compared, and it was found that the design effect for cluster sampling was larger that for the other methods, as expected. Survey cost information is needed to further inform discussion of the usefulness of the different methods. We assessed the extent of poverty by calculating the poverty index for the Tigray region. To calculate the poverty index we used the method proposed by the United Nations Development Programme (UNDP). Using the Welfare/Poverty Monitoring Survey year 2000 (WMS2000) data obtained from CSA, we found that the region is highly affected by each of the dimensions investigated. Further questions need to be added to questionnaires in order to allow use of the census data in calculating poverty maps.

by Lau Lap Cheung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1989. / Bibliography: leaves 123-124.

by Choy Sai Tsang Boris. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1992. / Includes bibliographical references (leaves 61-62). / Chapter CHAPTER 1 : --- Introduction and Review --- p.1 / Chapter § 1.1 : --- Introduction --- p.1 / Chapter § 1.2 : --- Review --- p.3 / Chapter CHAPTER 2 : --- Model and Bayes Risk for Random Censoring --- p.9 / Chapter § 2.1 : --- Model and Likelihood Function --- p.9 / Chapter § 2.2 : --- Decision Function and Loss Function --- p.11 / Chapter § 2.3 : --- Bayes Risk for Random Censoring with Uniformly Distributed Censoring Time --- p.12 / Chapter CHAPTER 3 : --- Searching for an Optimal Sampling Plan --- p.16 / Chapter § 3.1 : --- Algorithm --- p.16 / Chapter § 3.2 : --- Discretization Method --- p.17 / Chapter § 3.3 : --- Example for Random Censoring --- p.17 / Chapter CHAPTER 4 : --- Sequential Number-Theoretic Method for Type I Censoring --- p.29 / Chapter § 4.1 : --- Introduction --- p.29 / Chapter § 4.2 : --- Number-Theoretic Method for Generating a Set of Uniformly Scattered Points --- p.29 / Chapter § 4.3 : --- Sequential Number-Theoretic Method for Optimization --- p.31 / Chapter § 4.4 : --- Example for Type I Censoring --- p.32 / Chapter CHAPTER 5 : --- "Comparisons amongst Type I, Type II and Random Censorings" --- p.45 / Chapter CHAPTER 6 : --- Discussions --- p.52 / APPENDIX --- p.54 / REFERENCES --- p.61