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The Cochran–Armitage test for trend, [1] [2] named for William Cochran and Peter Armitage, is used in categorical data analysis when the aim is to assess for the presence of an association between a variable with two categories and an ordinal variable with k categories.
In the current example where tied scores only appear in adjacent groups, the value of S is unchanged if the ties are broken against the alternative hypothesis. This may be verified by substituting 11 mph in place of 12 mph in the Bumped sample, and 19 mph in place of 20 mph in the Smashed and re-computing the test statistic.
Unit-weighted regression is a method of robust regression that proceeds in three steps. First, predictors for the outcome of interest are selected; ideally, there should be good empirical or theoretical reasons for the selection.
Unpaired samples are also called independent samples. Paired samples are also called dependent. Finally, there are some statistical tests that perform analysis of relationship between multiple variables like regression. [1] Number of samples: The number of samples of data. Exactness: A test can be exact or be asymptotic delivering approximate ...
Strictly speaking, this interpretation is applicable for the estimation time frame only. Outside of this time frame, it cannot be determined how these immeasurable factors behave both qualitatively and quantitatively. Research results by mathematicians, statisticians, econometricians, and economists have been published in response to those ...
The logarithm is often favored because it is easy to interpret its result in terms of "fold changes". The logarithm also has a useful effect on ratios. If we are comparing positive quantities X and Y using the ratio X / Y , then if X < Y , the ratio is in the interval (0,1), whereas if X > Y , the ratio is in the half-line (1,∞), where the ...
For the "no effect" analysis, application of the least squares method for the segmented regression analysis [6] may not be the most appropriate technique because the aim is rather to find the longest stretch over which the Y-X relation can be considered to possess zero slope while beyond the reach the slope is significantly different from zero ...
The F-test in ANOVA is an example of an omnibus test, which tests the overall significance of the model. A significant F test means that among the tested means, at least two of the means are significantly different, but this result doesn't specify exactly which means are different one from the other.