X-radiation (composed of X-rays) is a form of electromagnetic radiation. Most X-rays have a wavelength ranging from 0.01 to 10 nanometers, corresponding to frequencies in the range 30 petahertz to 30 exahertz (3×1016 Hz to 3×1019 Hz) and energies in the range 100 eV to 100 keV. X-ray wavelengths are shorter than those of UV rays and typically longer than those of gamma rays. In many languages, X-radiation is referred to with terms meaning Röntgen radiation, after Wilhelm Röntgen, who is usually credited as its discoverer, and who had named it X-radiation to signify an unknown type of radiation. Spelling of X-ray(s) in the English language includes the variants x-ray(s), xray(s), and X ray(s).
X-rays with photon energies above 5–10 keV (below 0.2–0.1nm wavelength) are called hard X-rays, while those with lower energy are called soft X-rays. Due to their penetrating ability, hard X-rays are widely used to image the inside of objects, e.g., in medical radiography and airport security. As a result, the term X-ray is metonymically used to refer to a radiographic image produced using this method, in addition to the method itself. Since the wavelengths of hard X-rays are similar to the size of atoms they are also useful for determining crystal structures by X-ray crystallography. By contrast, soft X-rays are easily absorbed in air; the attenuation length of 600 eV (~2nm) X-rays in water is less than 1 micrometer.
The book, subtitled as an "unauthorized autobiography," employs a nameless 19-year-old first-person narrator hired by 'the Corporation' to seek out and interview a slightly demented geriatric version of Davies himself ten to twenty years after the time of the novel's publication. Thus, while technically an autobiography, the work has an unreliable narrator. In many ways a work of fiction, it reveals many factual details concerning the Kinks and other important figures of the swinging sixties, but tends to do so in a literary fashion. By employing this narrative device, Davies was able to shed some light on the life of the Kinks without resorting to the usual pedestrian 'he said/she said' mechanics often associated with memoirs of celebrities.
Instruments shows a time line displaying any event occurring in the application, such as CPU activity variation, memory allocation, and network and file activity, together with graphs and statistics. Group of events are monitored via customizable "instruments", which have the ability to record user generated events and replay (emulate) them exactly as many times as needed, so a developer can see the effect of code changes without actually doing the repetitive work. The Instrument Builder feature allows the creation of custom analysis instruments.
Built-in instruments can track
User events, such as keyboard keys pressed and mouse moves and clicks with exact time.
In baseballstatistics, an error is an act, in the judgment of the official scorer, of a fielder misplaying a ball in a manner that allows a batter or baserunner to advance one or more bases or allows an at bat to continue after the batter should have been put out.
The term error can also refer to the play during which an error was committed.
Relationship to other statistical categories
An error does not count as a hit but still counts as an at bat for the batter unless, in the scorer's judgment, the batter would have reached first base safely but one or more of the additional base(s) reached was the result of the fielder's mistake. In that case, the play will be scored both as a hit (for the number of bases the fielders should have limited the batter to) and an error. However, if a batter is judged to have reached base solely because of a fielder's mistake, it is scored as a "hit on error," and treated the same as if a batter was put out, hence lowering his batting average.
In statistics and optimization, errors and residuals are two closely related and easily confused measures of the deviation of an observed value of an element of a statistical sample from its "theoretical value". The error (or disturbance) of an observed value is the deviation of the observed value from the (unobservable) true value of a quantity of interest (for example, a population mean), and the residual of an observed value is the difference between the observed value and the estimated value of the quantity of interest (for example, a sample mean). The distinction is most important in regression analysis, where it leads to the concept of studentized residuals.
Suppose there is a series of observations from a univariate distribution and we want to estimate the mean of that distribution (the so-called location model). In this case, the errors are the deviations of the observations from the population mean, while the residuals are the deviations of the observations from the sample mean.