Correlation. By executing the Contract, the Contractor represents that he has visited the site, familiarized himself with the local conditions under which the Work is to be performed, and correlated his observations with the requirements of the Contract Documents.
Correlation. Design-Builder shall interpret Contract Documents as complementary, requiring a complete Project. Any requirement occurring in any one of the Contract Documents is as binding as though occurring in all Contract Documents. Generally, the Specifications address quality, types of materials and Contract conditions while the Plans show placement, sizes, and fabrication details of materials.
Correlation. At Avanex's option, correlation of test programs/procedures between Avanex and CMI shall be completed prior to Avanex's first customer shipment ("FCS") of an Avanex product containing Product. In the event of a conflict between test results, Avanex's test method, programs and analysis shall prevail. Details and specific procedures of the correlation plan between Avanex and CMI will be as mutually defined and agreed to by the parties.
Correlation. There appears to be a correlation between: (1) the conception of pupil voice lacking adult agency and/or (2) a deficit model of childhood and (3) tokenistic use or absence of pupil voice. Reconnecting with Xxxxxxxx’x quote in Chapter 3: ‘if I think that there is a mouse under the table then I will behave as though there is, whether or not there is in fact a mouse” (Xxxxxx et al, 2014: 220). This research reveals participants’ perceptions of pupil voice, whether factual or not, and how they are impacting their use or non-use of it.
Correlation. Correlation between Sustained Attention to Response Task (SART) error score and Multiple Sleep Latency Test (MSLT) sleep latency. Circles represent controls, triangles represent patients. In the figure, the 5-error cutoff point of the SART and the 5-minute cutoff point of the MSLT are indicated by a line. There was no significant correlation between SART error score and MSLT sleep latency. using the SART to distinguish between such disorders causing sleepiness; we contend that it is of use to measure vigilance. There were diurnal effects on SART performance and MSLT latency. In controls, the noon MSLT latency was shorter than that of earlier MSLT periods, as has been found in earlier studies.27-29 This effect was not significant in patients. In controls, the 9:00AM SART error score was significantly higher than that of other times. A possible explanation is that this reflects a brief learning effect, not fully covered by the 30-second introductory session. Another cause could be a diurnal effect. This effect meant that SART error scores of patients and controls were closer together at 9:00 AM than at other times, but there was still a clear difference at this time as well (Figure 7.2b).
Correlation f90:xxxxxxx xxxx vect : calculates the Xxxxxxx correlation of two vec- tors. This routine relies on BLAS, an optimized linear algebra library. Because of the limited number of degrees of freedom of the time series, the statistical significance of this estimate should be tested under the null hypothesis of zero-correlation.
Correlation. Licensee shall interpret Contract Documents as complementary, requiring a complete Project. Any requirement occurring in any one of the Contract Documents is as binding as though occurring in all Contract Documents. Generally, the Specifications address quality, types of materials and Contract conditions while the Plans show placement, sizes, and fabrication details of materials.
Correlation. To examine tobacco smoking as potential source of heavy metals, the correlations of those metals and cotinine were carried out. As we can see from Table 10, the results from Xxxxxxx correlation revealed that there was a positive linear relationship between natural log- transformed of urinary lead and cotinine with statistical significance (p-value <0.001, r=0.38). While the other pairs such as natural log-transformed urinary cotinine and cadmium (p-value 0.88, r=0.02) as well as natural log-transformed urinary cadmium and lead (p-value 0.69, r=- 0.69) did not show a significantly linear relationship.
Correlation. Table 7 shows pairwise correlations between greenness and a set of indicators for environmental policy, environmental degradation and innovation. The pairwise correlation highlights if a linear relationship between greenness and each variable of interest is present: the closer the correlation coefficient is to 1, the stronger the linear relation between two variables. A star near the coefficients indicates that the correlation is significant at the 95% level. Table 7 - Pairwise correlation Variables Greennes s Energy prices (all) Energy prices EPS CO2 Patent appl. Stock Patent applications Greenness 1.000 Energy prices (all) 0.057 1.000 Energy prices 0.126* 1.000* 1.000 EPS 0.106* -0.060 0.106 1.000 CO2 0.146* 0.091 0.165* 0.155* 1.000 Patent appl. Stock -0.004 -0.065 0.084 0.291* 0.500 * 1.000 Patent applications -0.007 -0.081 0.072 0.277* 0.505 * 0.988* 1.000 Note: * denotes significant correlation ant the 95% level Overall, we note that the simple correlations of greenness with other variables (first column of Table 7) are low. Nevertheless, in Table 7 the correlation is significant and positive between greenness and energy prices and greenness and EPS as well as between greenness and CO2 emissions. In Tables 8 to 10 we shed more light on these relationships by computing conditional correlations setting up a simple fixed effect regression which allows also to conditions on unobserved factors that can affect the association. Table 8 presents the conditional correlations between greenness and the set of policy indicators: columns 1 to 4 show association with energy prices using sector and time fixed effects, while conditional correlation with EPS (columns 5 and 6) are computed at the country level. In fact, while the latter is an indicator designed to capture policy stringency at the country level, energy prices are a better proxy for policy at the sector level. The main idea in Xxxx et al., (2019) is that energy prices increases as environmental policies become more stringent. As shown in columns 1 to 4, we employ two indicators, Energy prices (all) and Energy prices, which differ for the number of fuels on which the weighted average is computed, as explained in Section 3. There is a positive association of energy prices with greenness: in column 2, we note that a 1% increase in energy prices is associated with 0.04% increase in greenness. However, when we condition on value added, the coefficient associated with energy prices is no longer significant. T...
