How accurate are laypeople’s intuitions about probability distributions of events? The economic and psychological literatures provide opposing answers. A classical economic view assumes that ordinary decision makers consult perfect expectations, while recent psychological research has emphasized biases in perceptions. In this work, we test laypeople’s intuitions about probability distributions. To establish a ground truth against which accuracy can be assessed, we control the information seen by each subject to establish unambiguous normative answers. We find that laypeople’s statistical intuitions can be highly accurate, and depend strongly upon the elicitation method used. In particular, we find that eliciting an entire distribution from a respondent using a graphical interface, and then computing simple statistics (such as means, fractiles, and confidence intervals) on this distribution, leads to greater accuracy, on both the individual and aggregate level, than the standard method of asking about the same statistics directly.

A straightforward intuitive user-friendly compact graphical interface, PreDICT (Premier DICVOL Tool) has been developed to take full advantage of the new capabilities of the most recent version of the DICVOL14 Indexing Software. The latter, an updated version of DICVOL04, includes optimizations, e.g. for monoclinic and triclinic cases, a detailed review of the input data from the indexing solutions, cell centering tests, as well as the handling of a moderate number of impurity peaks. Among the most salient features of PreDICT, one can mention the ability (1) to use 2θ non-equistepped input 1D X-ray powder diffraction patterns as can be obtained from 2D detectors, (2) to strip laboratory data from its Kα2 contribution when present, (3) to generate 2θ equistepped output 1D X-ray powder diffraction patterns in both the “.XY” and “.GSA” formats. In addition, PreDICT allows for the following features: (1) full access to the native DICVOL14 input/output ASCII file system is retained, (2) for any selection of a DICVOL14 suggested unit cell, all predicted Bragg peaks up to a certain 2θMAX value are clearly displayed and indicated, thereby emphasizing the contribution of the unaccounted peaks (if any) to the 1D X-ray powder diffraction pattern under current investigation.

PDM13 is a new graphic interface program dedicated to frequency domain analysis based on the Phase Dispersion Minimization technique (PDM, Stellingwerf 2012). In this paper, we will present the different algorithms running in PDM13, including the Auto-Segmentation, the Gauss-Newton and the PDM algorithms. More details on this triptych are available in our recent paper (Zalian et al., submitted). Their aim is to offer a simple and powerful way to extract frequency. Amongst the numerous improvements offered by the program, we will particularly focus on the reduction of aliases and the ability to look directly for multiple-period phenomena and the Blazhko effect. After that, we will show the first results from PDM13 using the Antarctica photometric survey.

A graphical robot programming system has been developed. This system with a graphical interface is user-friendly and easy-to-learn for low-skill users. It has been developed as a prototype system under a project by the Japan Robot Association (JARA) since 1994. The system runs on a personal computer and consists of a graphical user interface and an editing system. It is designed for programming an arc welding robot in small batch production and is expected to provide low-skill users with a means to use industrial robots with ease.