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One-way analysis of variance (ANOVA) was used to examine differences in the parametric data among the three groups.
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This inherent difference leads to the difference in the parametric statistical methods that are used since they often depend on the assumptions of the random mechanism that generates the data.
The spurious signal generated as a result of nonlinearity at the receiving system affects the measurement of the difference-frequency sound in the parametric loudspeaker, especially in the nearfield or near the beam axis.
While keeping that in mind, we find that difference-in-difference parametric models yielded somewhat higher point estimates with respect to their counterpart matching approach, particularly for men.
The t-test or Mann-Whitney test was used to detect differences in the distribution of continuous parametric variables.
As shown in Figure 2 for daily new cases, the differences in the estimates based on parametric approach with Gamma distribution and those with nonparametric approaches were minor.
Maternal age, income, education, employment status and ethnicity were similar in both cities (Table 2) and though Calgary had a slightly higher SES there were no significant differences in the data using non-parametric statistical analysis (Fisher's exact test and Chi-square).
Group differences in continuous parametric variables (eg, age) were examined with the Student t test or 1-way ANOVA as appropriate.
Differences in the prediction accuracy of non-parametric and linear models (at least for the data sets included in this and other studies) seem to be more pronounced in wheat than in maize.
However, minor individual differences in the shape of the responses suggest parametric differences between subjects.
Mean differences in the change values (or their non-parametric equivalents, depending on the distribution of the change values) will then be calculated for each of the three impairment groups.
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