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Video Retoucher in Dark Photo Theme Related Posts After Effects Seven YouTube tutorial Paradise Effects 7 YouTube tutorial the partial F-test is used, the numbers of means that are pooled, compared and combined are the same in both cases. In the experimental analysis section we discuss how these numbers are related to the statistical significance of the F-test results. Confidence interval validation ============================== The correspondence between different calculations of confidence intervals for treatments and controls was examined. As already mentioned in the [Methods](#s2){ref-type=”sec”} section, the student t-test is used to calculate paired two sample t-tests to measure the differences between treatments and their controls. To compare each treatment to its own control, the controls and their corresponding treatments are paired together. The confidence interval can be derived using the Student t-distribution with the means and variances of the two samples. In the case of two or more treatments being compared to a single control, the confidence interval can be calculated as a multiple of the standard error for each of the treatments. In the case of the two sample t-test, it is possible to choose different degrees of confidence to calculate confidence intervals. However, it is important to note that all t-tests are by design small sample t-tests. In a small sample test there is a probability of 0.05 of measuring an effect (the hypothesis will be rejected) if the population effect is smaller than the measured effect [@pone.0078206-Nathani1]. Thus, it is impossible to expect results with any better than 1% probability. When comparing two groups (or a group and its control) with two sample t-tests, the use of a confidence interval is complicated by the fact that the sampling distribution of the t-statistic is not normally distributed. The two sample t-test is not a standardized test with a standardized t-statistic and standard error. It would be possible to use the Student t-distribution to calculate confidence intervals for the t-statistic as if the t-distribution was normally distributed. However, this would not yield a confidence interval for the differences between two groups. In fact, it would even yield negative confidence intervals for the differences between two groups. The confidence intervals for the differences between two groups do not have a known joint distribution [@pone.0078206-Manning1]. The central limit theorem says that when the
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