The questionnaires from the field were received, checked and stored by the data processing personnel. They checked: 1. The completeness of the questionnaires 2. The correct bubbling 3. The correct number of questionnaires per household, if total males + total females > 8 as the questionnaire ONLY accommodated maximum of 8 household members. 4. The reference number appears in all the 10 pages of the questionnaires.

Population and Housing Census

This introductory text on the design and analysis of sample surveys emphasizes the practical aspects of survey problems. It begins with brief chapters on the role of sample surveys in the modern world. Thereafter, each chapter introduces a sample survey design or estimation procedure by describing the pertinent practical problem. The authors describe the methodology proposed for solving the problem and provide the details of the estimation procedure, including a compact presentation of the formulas needed to complete the analysis. Then, a practical example is worked out in complete detail. At the end of each chapter, a wealth of exercises gives students ample opportunity to practice the techniques and stretch their grasp of ideas.

Elementary Survey Sampling

Introduction to quality engineering : designing quality into products and processes

The modeling of extreme values is important to scientists in such  elds as hydrology, civil engineering, environmental science, oceanography and  nance. Stuart Coles’s book on the modeling of extreme values provides an introductory text on the topic. It is a modeling-oriented text with an emphasis on different types of data and analytical approaches. The book is laid out in nine chapters. Following introductory material and discussion of necessary theoretical background are chapters on approaches to extreme values that focus on the different types of data that might be used in an extreme value analysis. These include models for block maximums, threshold models, models for data from stationary and nonstationary processes, and approaches based on point processes. A chapter covers analysis of multivariate extremes, and the  nal chapter brie y covers such topics as Bayesian inference, Markov chains, and spatial extremes. Although this is not a data-driven text, it does contain numerous examples and analyses. These examples are used to illustrate the methodology; I would have preferred to see more motivation and interpretation of the results of the analyses. Datasets and S-PLUS programs for the analyses in the text are available at a website. These are easy to use for those slightly familiar with S-PLUS. The appendix describes the programs and illustrates how to access data and use the programs. It also gives links to sites that provide other software. The text does not include problem sets; these would have been useful, especially if the text is to be used in coursework. The text by Reiss and Thomas (2001) contains more thoroughly analyzed datasets, although it is twice the length and not as streamlined as the text under review. The book is meant for individuals with moderate statistical background. Those with coursework in maximum likelihood methods should have no dif culty reading and comprehending the text. Overall, this is a good text for someone getting started in extreme value methods.

Statistical Quality Control

Μελέτη των διαταραχών του λόγου σε ασθενείς με ανοϊκά σύνδρομα με τη χρήση του Western Aphasia Battery - Revised

An overview is given of the literature on Phase I parametric control charts for univariate variables data. When designing the charts, the joint distribution of the charting statistics is used to control the false alarm probability. An example is given a..

Phase I Statistical Process Control Charts: An Overview and Some Results

Control charts that are based on assumption(s) of a specific form for the underlying process distribution are referred to as parametric control charts. There are many applications where the...

Nonparametric (distribution-free) control charts: An updated overview and some results

Distribution-free (nonparametric) control charts provide a robust alternative to a data analyst when there is lack of knowledge about the underlying distribution. A two-sided nonparametric Phase II exponentially weighted moving average (EWMA) control chart, based on the exceedance statistics (EWMA-EX), is proposed for detecting a shift in the location parameter of a continuous distribution. The nonparametric EWMA chart combines the advantages of a nonparametric control chart (known and robust in-control performance) with the better shift detection properties of an EWMA chart. Guidance and recommendations are provided for practical implementation of the chart along with illustrative examples. A performance comparison is made with the traditional (normal theory) EWMA chart for subgroup averages and a recently proposed nonparametric EWMA chart based on the Wilcoxon-Mann-Whitney statistics. A summary and some concluding remarks are given.

Distribution-free exponentially weighted moving average control charts for monitoring unknown location

https://repository.up.ac.za/bitstream/handle/2263/18960/Graham_Distribution%282012%29.pdf?sequence=1

https://repository.up.ac.za/bitstream/handle/2263/18959/Graham_Nonparametric%282011%29.pdf?sequence=1

Marien Alet Graham

Papers

Phase I Statistical Process Control Charts: An Overview and Some Results

Nonparametric (distribution-free) control charts: An updated overview and some results

Distribution-free exponentially weighted moving average control charts for monitoring unknown location

Distribution-free exponentially weighted moving average control charts for monitoring unknown location

A nonparametric exponentially weighted moving average signed-rank chart for monitoring location