An Analysis of the Telecommunications Business in China by Linear Regression

In this paper, we study the influence of the National Telecom Business Volume by the data in 2008 that have been published in China Statistical Yearbook of Statistics. We illustrate the procedure of modeling “National Telecom Business Volume” on the following eight variables, GDP, Consumption Levels, Retail Sales of Social Consumer Goods Total Renovation Investment, the Local Telephone Exchange Capacity, Mobile Telephone Exchange Capacity, Mobile Phone End Users, and the Local Telephone End Users. The testing of heteroscedasticity and multicollinearity for model evaluation is included. We also consider AIC and BIC criterion to select independent variables, and conclude the result of the factors which are the optimal regression model for the amount of telecommunications business and the relation between independent variables and dependent variable. Based on the final results, we propose several recommendations about how to improve telecommunication services and promote the economic development.

Rekrytering av kreatörer och portfolions betydelse : En enkätundersökning med femtio svenska kommunikationsbyråer

Inom kommunikationsbranschen råder det hög konkurrens om arbeten för både nyutexaminerade arbetssökande och de med erfarenhet. En viktig del i ansök-ningshandlingarna är en portfolio som visuellt visar personens kompetens och talang.Denna kvantitativa studie har genom en webbenkät med 50 byråer inom kom-munikationsbranschen undersökt hur de rekryterar ny personal samt deras per-spektiv kring portfolion i samband med detta. Studien har även syftat till att belysa skillnader i svaren beroende på byråernas storlek.Resultaten från enkäten visade att den vanligaste kanalen vid anställning inom kommunikationsbranschen är via personliga kontakter och att det är portfolions kvalité som väger tyngst vid anställning. Vid ansökan föredrog byråerna en digital portfolio men vid en arbetsintervju såg de helst en kombination av en fysisk och digital portfolio. Mindre skillnader fanns i svaren beroende på byrå-storleken.

Recent developments in statistical methods for detecting genetic loci affecting phenotypic variability

A number of recent works have introduced statistical methods for detecting genetic loci that affect phenotypic variability, which we refer to as variability-controlling quantitative trait loci (vQTL). These are genetic variants whose allelic state predicts how much phenotype values will vary about their expected means. Such loci are of great potential interest in both human and non-human genetic studies, one reason being that a detected vQTL could represent a previously undetected interaction with other genes or environmental factors. The simultaneous publication of these new methods in different journals has in many cases precluded opportunity for comparison. We survey some of these methods, the respective trade-offs they imply, and the connections between them. The methods fall into three main groups: classical non-parametric, fully parametric, and semi-parametric two-stage approximations. Choosing between alternatives involves balancing the need for robustness, flexibility, and speed. For each method, we identify important assumptions and limitations, including those of practical importance, such as their scope for including covariates and random effects. We show in simulations that both parametric methods and their semi-parametric approximations can give elevated false positive rates when they ignore mean-variance relationships intrinsic to the data generation process. We conclude that choice of method depends on the trait distribution, the need to include non-genetic covariates, and the population size and structure, coupled with a critical evaluation of how these fit with the assumptions of the statistical model.