GCP Historical Background


Again the difference was significant. Such data are removed. In addition to the descriptions, the website is the repository for our primary analyses and summaries, and it provides access to the data.

Establishing the EGG Project


Schiltach ots - Zum Jahresbeginn präsentiert sich die Hansgrohe Group mit ihrem neuen Das Angebot besteht für den Zeitraum vom 3. Oktober bis 2. Das Gebiet hat eine Grösse von Die Wassertiefen schwanken grösstenteils zwischen und Metern und sind daher durchaus in Reichweite für die momentan verfügbare, bewährte Technologie der Unterwasserölbohrungen.

Seismische Untersuchungen und andere geophysikalische Messungen lassen erkennen, dass sich Öl- und Gasvorkommen im Dreki-Gebiet befinden könnten, da in angrenzenden, geologisch ähnlichen Gebieten solche Funde zu verzeichnen waren. Weitere Untersuchungen einschliesslich Explorationsbohrungen sind erforderlich, um Öl- oder Gasvorkommen im Dreki-Gebiet nachweisen zu können. Strenge Sicherheitsanforderungen und Arbeitsschutzbestimmungen werden vorhanden sein, sowie auch Umweltauflagen, die denen in Nachbarstaaten ähneln.

Eine Neuinstallation von Treibern und Launch Manager hat bis jetzt nichts gebracht.. Wäre toll wenn mir jemand helfen könnte. Seit Windows 10 funktionieren meine Fn Tasten nicht mehr? Wie kann ich dieses Problem beheben? Vom Fragesteller als hilfreich ausgezeichnet. Gummileder Ja nur finden tut er nix, er ist installiert ja ständig neue Updates.

Gummileder Um welche Software handelt es sich denn, wo diese Funktionsweise steuert? Showmustgoon Wenn die Acer Website nicht so schlecht gemacht wäre, hätte ich dir ja einen Link geschickt.

Gummileder Das werde ich dann mal ausprobieren. Showmustgoon Das hier ist die Suppoprt Seite für das Gerät https: Gummileder Nur leider nicht kompatibel für Windows 10, soll ich dennoch herunterladen ohne dass bleibende Schäden entstehen? Showmustgoon Der Launch Manager ist nun auf meinem System vorhanden.

Darf ich die weiteren Schritte erfahren? Showmustgoon Funktioniert immer noch nicht? Gummileder Nein, das Problem wurde somit leider nicht behoben. Was möchtest Du wissen? The goal is to determine whether any correlations might be detectable of statistics from these data with independent long-term physical or sociological variables.

In the original experimental design we asked the more limited question whether there is a detectable correlation of deviations from randomness with the occurrence of major events in the world. Periods of collective attention or emotion in widely distributed populations will correlate with deviations from expectation in a global network of physical random number generators.

The formal hypothesis of the original event-based experiment is very broad. It posits that engaging global events will correlate with deviations in the data. We use operational definitions to establish unambigously what is done in the experiment. The identification of events and the times at which they occur are specified case by case, as are the statistical recipes.

The approach explicitly preserves some latitude of choice, as is appropriate for an experiment exploring new territory. Accepting loose criteria for event identification allows exploration of a variety of categories, while the specification of a rigorous, simple hypothesis test for each event in the formal series assures valid statistics. These are combined to yield a confidence level for the composite of all formal trials.

This bottom line constitutes a general test of the broadly defined formal hypothesis, and characterizes a well-understood database for further analysis. The formal events are fully specified in a hypothesis registry. Over the years, several different analysis recipes were invoked, though most analyses specify the network variance Squared Stouffer Z.

After the first few months, during which several statistical recipes were tried, the network variance netvar became the standard method which was adopted for almost all events in the formal series. The event-based experiment thus has explored several potentially useful analyses, but has focused primarily on the netvar.

The event statistics usually are calculated at the trial level—1 second—though other blocking is possible. The trial statistics are combined across the total time of the event to yield the formal result.

The results table has links to details of the analyses, typically including a cumulative deviation graph tracing the history of the second-by-second deviations during the event, leading to the terminal value which is the test statistic. The following table shows the precise algorithms for the basic statistics used in the analyses. It is possible to generate various kinds of controls, including matched analysis with a time offset in the actual database, or matched analysis using a pseudorandom clone database.

However, the most general control analysis is achieved by comparisons with the empirical distributions of the test statistics. These provide a rigorous control background and confirm the analytical results for the formal series of hypothesis tests. See the figure below, created by Peter Bancel using a reduced dataset beginning December and ending December , which compares the cumulative formal result against a background of resampled controls.

Over the 12 years since the inception of the project, over replications of the basic hypothesis test have been accumulated. The composite result is a statistically significant departure from expectation of roughly 6 standard deviations as of late This strongly supports the formal hypothesis, but more important, it provides a sound basis for deeper analysis using refined methods to re-examine the original findings and extend them using other methods.

The full formal dataset as of April is shown in the next figure, where it is compared with a background of simulated pseudo-event sequences by drawing random Z-scores from the 0,1 normal distribution. As in the resampling case, it is obvious that the real data are from a different population. Note, however, that it takes a few dozen events to reach a point where the real score accumulation is clearly distinguishable from the simulations.

The focus of our effort turns now to a more comprehensive program of rigorous analyses and incisive questions intended to characterize the data more fully and to facilitate the identification of any non-random structure. We begin with thorough documentation of the analytical and methodological background for the main result, to provide a basis for new hypotheses and experiments.

The goal is to increase both the depth and breadth of our assessments, to develop models that can help distinguish classes of potential explanations.

Essentially, we are looking for good tools that will give us a better understanding of the data deviations. A variety of analyses have been undertaken to establish the quality of the data and characterize the output of individual devices and the network as a whole. The first stage is a careful search for any data that are problematic because of equipment failure or other mishap.

Such data are removed. With all bad data removed, each individual REG or RNG can be characterized to provide empirical estimates for statistical parameters. This also allows a shift of analytical emphasis from the events to trial-level data in order to extract more structural information from the database.

The approach is to convert the database into a normalized, completely reliable data resource that facilitates rigorous analysis. The trial-level data allow a richer assessment of the multi-year database using sophisticated statistical and mathematical techniques.

We can use a broader range of statistical tools to look for small but reliable changes from expected random distributions that may be correlated with natural or human-generated variables.

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