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Magister Philosophiae - MPhil / In many countries, an enumeration of all household members remains the most important source of population statistics. According to Statistics South Africa, two population censuses and quite a few household surveys have taken place across the country. The quality of data recorded varies according to the operation. Despite great improvement in data collection and analysis capacities,some of the demographic data provided have not been assessed in terms of quality. The aim of this study was to ascertain the accuracy of demographic data on age and sex collected and the coverage during the population census 2001, General Household Surveys (2004 and 2007), Labour Force Surveys (2005 and 2007) and Community survey 2007 in South Africa. Two methods were applied to assess the quality of data. First, the direct method consists of checking the content and coverage (errors during enumeration, errors of exploitation, concordance in questionnaire). Second, the indirect method lies in the calculation of some indexes, age ratios,sex ratios, graphing of population pyramids and sex ratios curves. The indexes are Whipple’s index, Myer’s index and the Combined index of United Nations. Therefore, the main variables of interest are age, sex, place of residence and ethnic groups. Differentials in the quality according to declaration on age by gender, by ethnic group, by place of residence have been explored. This study has identified some variations in different indexes between 2001 and 2007 and has also evaluated the ethnic, gender and regional differentials. Comparison between indexes of each instrument has been done to measure some variations over years. Also, time-space comparisons were conducted across indexes of different instruments. The quality of data on age was better at national level compared to provincial level. Therefore, based on the measurements and patterns observed in the census and surveys data, the study has made some recommendations on the need for an integrated approach to reduce the gap and improve the quality of declarations on age and sex.

Warren Buffet started an investment partnership of $100 in 1956 and has gone on to accumulate a personal net worth of over $60 billion. He started primarily as a value investor, and gradually changed over time to a strategy which uses the PEG ratio as its main tool. Peter Lynch, one of the most successful fund managers in history and had a compound annual growth rate of 29% for 13 years, was the man to first introduce the world to the PEG ratio. With such prominence, however, widespread use of previously successful strategies tend to render them ineffective due to everyone using them, and today the PEG ratio’s effectiveness as a valuation tool remains a topical debate between market commentators.This study sets out to determine if the PEG ratio adds value using JSE Main Board data from 2002 to 2012. Returns from five portfolios constructed directly from share quintiles based on PEG ratio magnitude are compared to returns of a portfolio constructed from the optimum quintile of value shares. The PEG ratio portfolio returns are examined based on 3 rebalancing period strategies, and on relative performance between the quintiles within each strategy.It is found that a 24 monthly rebalancing strategy provides superior returns to that of 3 or 12 monthly rebalancing for PEG quintiles of selected stocks. Furthermore, the lowest PEG ratio quintile in this strategy outperforms the value portfolio by a compound annual growth rate of 4.3%. The second lowest PEG ratio quintile portfolio performs slightly better to ensure that 40% of stocks selected based on the PEG ratio produced sustained superior returns to the optimum quintile value portfolio. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

Astragalus ampullarioides and A. holmgreniorum are two rare endemics of southwestern Utah. Over two consecutive field seasons (2009-2010) we examined pre-emergent reproductive success, based on F/F and S/O ratios, from populations of both Astragalus ampullarioides and A. holmgreniorum, estimated the density of the soil seed bank of A. holmgreniorum as a measure of potential post-emergent reproductive success, and estimated seed persistence within the soil seed bank. Fruit/flower (F/F) ratios and seed/ovule (S/O) ratios varied significantly between populations and among years in both species, and showed low reproductive output in both taxa. In Astragalus ampullarioides F/F and S/O were 0.06±0.01 and 0.16±0.02, respectively (2009), and 0.14±0.01 and 0.41±0.02, respectively (2010). For Astragalus holmgreniorum F/F and S/O ratios were 0.11±0.01 and 0.38±0.02, respectively (2009), and 0.23±0.01 and 0.66±0.02, respectively (2010). Although Astragalus holmgreniorum exhibited a low soil seed bank density (4.3 seeds m-2), seed persistence data showed low a low percentage of seeds germinated during the first year in the soil seed bank. Seeds remaining in the seed bank maintained high percent viability. Soil seed persistence of Astragalus ampullarioides differed from A. holmgreniorum in that a high percentage of seeds germinated during the first year in the soil seed bank. A high percentage of viability in ungerminated seeds was also maintained in A. ampullarioides. Although these species differ in life histories and dependence on soil seed banks, an understanding of the strategies unique to each species will prove useful in management plans.

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No / Medical statistics is a vast and ever-growing field of academic endeavour, with direct application to developing the robustness of the evidence base in all areas of medicine. Although the complexity of available statistical techniques has continued to increase, fuelled by the rapid data processing capabilities of even desktop/laptop computers, medical practitioners can go a long way towards creating, critically evaluating and assimilating this evidence with an understanding of just a few key statistical concepts. While the concepts of statistics and ethics are not common bedfellows, it should be emphasised that a statistically flawed study is also an unethical study.[1] This review will outline some of these key concepts and explain how to interpret the output of some commonly used statistical analyses. Examples will be confined to two-group tests on independent samples, using both a continuous and a dichotomous/binary outcome measure.