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harley credited the look of world war ii fighter aircraft for his inspiration, particularly the twin-tailed p-38 lightning.
Позднее сам Эрл уточнил, что вдохновением для него послужил американский двухбалочный истребитель времен Второй мировой войны p-38 lightning.
after completing the project, the actual data can be used to find the p-value at which the project was executed allowing users to make more accurate estimates in the future.
После окончания строительства фактические данные можно использовать для расчета р-значения, при котором был реализован проект. Это значение используется для уточнения расчетов стоимости при строительстве будущих скважин.
figure 7 demonstrates this concept: the flat lying event has an higher amplitude on the far traces, thus we cannot reconstruct it with a single p value, as other trajectories are required so as to constructively sum to build the greater amplitudes on the far offsets.
На Рис. 7 наглядно показано, что плоский сигнал (плоское пятно) характеризуется более высокой амплитудой по дальним трассам, а, следовательно, восстановление такого сигнала по одному значению р невозможно. В данном случае необходимо использовать дополнительные траектории для эффективного суммирования с целью получения более широкого диапазона амплитуд на больших удалениях.
\<ahelp hid=\"hid_func_gtest\"\>returns the two-tailed p value of a z test with standard distribution.\</ahelp\>
\<ahelp hid=\"hid_func_gtest\"\>Вычисляет двухстороннюю вероятность значений z теста при стандартном распределении.\</ahelp\>
if we ignore the aspect of smearing in the transform, then we can see that the input data can be represented by just seven unique ‘p’ value traces, rather than the original 100 input seismic traces: this constitutes data compression.
Если не принимать во внимание эффект размывания при преобразовании, то исходные данные можно представить с помощью всего семи трасс значений р, а не использовать все 100 исходных сейсмотрасс. Такую операцию называют сжатием данных.
for example, the z-test (ztest) and the t-test (ttest) both assume that the data are independently sampled from a normal distribution. statistics toolbox functions are available for testing this assumption, such as chi2gof, jbtest, lillietest, and normplot. both the z-test and the t-test are relatively robust with respect to departures from this assumption, so long as the sample size n is large enough. both tests compute a sample mean , which, by the central limit theorem, has an approximately normal sampling distribution with mean equal to the population mean μ, regardless of the population distribution being sampled. the difference between the z-test and the t-test is in the assumption of the standard deviation σ of the underlying normal distribution. a z-test assumes that σ is known; a t-test does not. as a result, a t-test must compute an estimate s of the standard deviation from the sample. test statistics for the z-test and the t-test are, respectively, under the null hypothesis that the population is distributed with mean μ, the z-statistic has a standard normal distribution, n(0,1). under the same null hypothesis, the t-statistic has student's t distribution with n – 1 degrees of freedom. for small sample sizes, student's t distribution is flatter and wider than n(0,1), compensating for the decreased confidence in the estimate s. as sample size increases, however, student's t distribution approaches the standard normal distribution, and the two tests become essentially equivalent. knowing the distribution of the test statistic under the null hypothesis allows for accurate calculation of p-values. interpreting p-values in the context of the test assumptions allows for critical analysis of test results. assumptions underlying statistics toolbox hypothesis tests are given in the reference pages for implementing functions.
最終更新： 2013-05-22
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