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This case study uses several univariate and multivariate statistical techniques to evaluate and interpret a water quality data set obtained from the Klang River basin located within the state of Selangor and the Federal Territory of Kuala Lumpur, Malaysia. The river drains an area of 1,288 km(2), from the steep mountain rainforests of the main Central Range along Peninsular Malaysia to the river mouth in Port Klang, into the Straits of Malacca. Water quality was monitored at 20 stations, nine of which are situated along the main river and 11 along six tributaries. Data was collected from 1997 to 2007 for seven parameters used to evaluate the status of the water quality, namely dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, ammoniacal nitrogen, pH, and temperature. The data were first investigated using descriptive statistical tools, followed by two practical multivariate analyses that reduced the data dimensions for better interpretation. The analyses employed were factor analysis and principal component analysis, which explain 60 and 81.6% of the total variation in the data, respectively. We found that the resulting latent variables from the factor analysis are interpretable and beneficial for describing the water quality in the Klang River. This study presents the usefulness of several statistical methods in evaluating and interpreting water quality data for the purpose of monitoring the effectiveness of water resource management. The results should provide more straightforward data interpretation as well as valuable insight for managers to conceive optimum action plans for controlling pollution in river water.

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<span>Electronic commerce has been growing at a rapid rate in many countries, including developing countries. In recent years, social media and social networking sites have become popular and such popularity has led to a novel e-commerce branch known as social commerce. In Malaysia, it is observed that individuals and organizations have begun to sell and purchase using social media. But studies on s-commerce adoption in Malaysia are still lacking. Therefore, this study aimed to investigate the effects of technological, organizational, and trust factors on social commerce adoption among SMEs in Malaysia. This paper presented the factors, collected from literature, which influence the adoption of social commerce, and the results of an exploratory pilot study.</span>

Abstract. The random vector of frequencies in a generalized urn model can be viewed as conditionally independent random variables, given their sum. Such a representation is exploited here to derive Edgeworth expansions for a "sum of functions of such frequencies", which are also called "decomposable statistics." Applying these results to urn models such as with-and withoutreplacement sampling schemes as well as the multicolor Pólya-Egenberger model, new results are obtained for the chi-square statistic, for the sample sum in a without replacement scheme, and for the so-called Dixon statistic that is useful in comparing 2 samples.