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Total lipid analysis concentration in percentages and Principal Component Analysis Figure.

Données pour évaluer la rentabilité du coton-Bt comparativement au coton conventionnel selon le niveau d'équipement en culture attelée dans la principale zone de production cotonnière du Burkina Faso

Quetelet’s data on Scottish chest girths are analyzed with eight normality tests. In contrast to Quetelet’s conclusion that the data are fit well by what is now known as the normal distribution, six of eight normality tests provide strong evidence that the chest circumferences are not normally distributed. Using corrected chest circumferences from Stigler, the χ2 test no longer provides strong evidence against normality, but five commonly used normality tests do. The D’Agostino–Pearson K2 and Jarque–Bera tests, based only on skewness and kurtosis, find that both Quetelet’s original data and the Stigler-corrected data are consistent with the hypothesis of normality. The major reason causing most normality tests to produce low p-values, indicating that Quetelet’s data are not normally distributed, is that the chest circumferences were reported in whole inches and rounding of large numbers of observations can produce many tied values that strongly affect most normality tests. Users should be cautious using many standard normality tests if data have ties, are rounded, and the ratio of the standard deviation to rounding interval is small.

There has been strong recent interest in testing interval null hypotheses for improved scientific inference. For example, Lakens et al. and Lakens and Harms use this approach to study if there is a prespecified meaningful treatment effect in gerontology and clinical trials, instead of a point null hypothesis of any effect. Two popular Bayesian approaches are available for interval null hypothesis testing. One is the standard Bayes factor and the other is the region of practical equivalence (ROPE) procedure championed by Kruschke and others over many years. This article connects key quantities in the two approaches, which in turn allow us to contrast two major differences between the approaches with substantial practical implications. The first is that the Bayes factor depends heavily on the prior specification while a modified ROPE procedure is very robust. The second difference is concerned with the statistical property when data are generated under a neutral parameter value on the common boundary of competing hypotheses. In this case, the Bayes factors can be severely biased whereas the modified ROPE approach gives a reasonable result. Finally, the connection leads to a simple and effective algorithm for computing Bayes factors using draws from posterior distributions generated by standard Bayesian programs such as BUGS, JAGS, and Stan.

FREE TRADE AGREEMENTS - This interactive infographic complements the JRC scientific report "Cumulative economic impact of trade agreements on EU agriculture – 2021 update", a study carried out by the European Commission - Joint Research Centre (JRC) that presents potential effects of twelve free trade agreements (FTAs) under the current EU FTA agenda. It sheds some light on the cumulated impacts in terms of trade, production and price for the EU agricultural sector as a whole, while quantifying also the market development for specific agricultural sectors. Different from a forecast exercise, it compares a conservative and an ambitious FTA scenario with a business as usual (reference) scenario. The study is presented to the Agriculture Council on 25th January 2021 and published contextually to the press conference on the 26th.

This study was a cross-sectional, web-based survey of Ontario paramedics that measured perceptions, support, interest, and training in Community Paramedicine (CP). Paramedics view multiple functions within the Community Paramedic role and are very supportive and interested in Community Paramedicine.

A variety of random graph models have been proposed in the literature to model the associations within an interconnected system and to realistically account for various structures and attributes of such systems. In particular, much research has been devoted to modeling the interaction of humans within social networks. However, such networks in real-life tend to be extremely sparse and existing methods do not adequately address this issue. In this article we propose an extension to ordinary and degree corrected stochastic blockmodels that accounts for a high degree of sparsity. Specifically, we propose hurdle versions of these blockmodels to account for community structure and degree heterogeneity in sparse networks. We use simulation to ensure parameter estimation is consistent and precise, and we propose the use of likelihood ratio-type tests for model selection. We illustrate the necessity for hurdle blockmodels with a small research collaboration network as well as the infamous Enron email exchange network. Methods for determining goodness-of-fit and performing model selection are also proposed.

Polar UDC, created largely by the Scott Polar Library at Cambridge, England, is a variant of Universal Decimal Classification. Polar UDC arranges materials by geography, rather than subject. A system of numerical classes, representing geographic regions overlays the standard UDC subject classification. This allows for the co-location, on shelves, of materials about a place, regardless of the subject. In this example, all of the books shown on the shelf are in class *440.2, which represents Nunavut, in Canada.

Abstract The ways border regimes affect migration patterns remain ambiguous. Closed borders may constrain migration but also encourage migrants to pursue alternative migration channels and destinations. While open borders may be associated with higher migration, oftentimes they promote circulation and return. To clarify how different border regimes influence migration patterns, this article examines the impact of open and closed border regimes on migration outcomes in Guyana, Suriname and French Guiana in the 1950s–1980s period, when all three gained independence or non-sovereign status and colonial ties were strong. The article proposes a conceptual schematic model that can accommodate varied post-colonial political and border regime transitions and explains changes in the timing, destination and composition of migration. The analysis finds that, counterintuitively, closed borders can lead to high emigration while open borders can encourage people to stay. The proposed model also illustrates the relevance of three dimensions of time: the historical juncture, the sequence of change and the time span. In sum, rather than preventing migration, border regimes yield important effects that lead to migration diversification.