Sentences with phrase «very weak correlation»

(i) Harrison and Stephenson show (see their Figure 2; reproduced in Figure 3 in top article) a very weak correlation between the CRF and the diffuse fraction (DF)(cloudiness — presumably dominated by changes in low - level cloudiness), which breaks down when the CRF is higher than 3600 (x100) per hour.

Sapone et al. performed both zonulin and lactulose — mannitol testing and found only a very weak correlation between the results of the two assessments (correlation coefficient = 0.36)(13).

Prior to the crisis, variation in the monetary base had a very weak correlation with stock returns even on a coincident basis.

Alternatively, the Work Pressure and Pace CPSPSC composite consistently had very weak correlations with all PP indices.

Not exact matches

The reason why the minimum wage does little for poverty is very simple — there is an incredibly weak correlation between a person's hourly wage and their family's monthly after - tax income.

For all the reasons listed above, the correlation between these two factors is actually very weak, as demonstrated by Tim Koller, Jack Murrin, and Thomas E. Copeland in Valuation: Measuring and Managing the Value of Companies (p. 80).

The correlation between these two series is a very weak -0.07.

«The correlation with amyloid plaque was there but very weak; not nearly as strong as the correlation between p - tau and cognitive decline.»

But, the second thing we found was that the correlation between a teacher's submitted lesson and their unsubmitted lessons was very high - about.75, which is just saying that the best lessons from the best teachers are that much better than the best lessons from the weakest teachers.

Hi Mike G — Correlations of.2 describe very weak relationships.

While these are also noted as statistically significant, using the table below one can determine that statistical significance does not necessarily mean that such «very weak» to «weak» correlations are of much practical significance, especially if and when high - stakes decisions about teachers and their effects are to be attached to such evidence.

These correlations, as they were in the previous article / post cited above, were statistically significant, positive, and fell in the very weak range in mathematics (0.15 < r < 0.19) and very weak range in English / language arts (0.07 < r < 0.15).

Indeed this is true, although the correlations they observed, as aligned with what is increasingly becoming a saturated finding in the literature (see similar findings about the Marzano observational framework here; see similar findings from other studies here, here, and here; see also other studies as cited by authors of this study on p. 13 - 14 here), is that the magnitude and practical significance of these correlations are «very weak» (e.g., r =.18) to «moderate» (e.g., r =.45,.46, and.48).

Weak correlation exists to higher VIX leading to higher returns but it is not very strong.

Simply put, the mathematical correlation between an increase in atmospheric CO2 and temperature is very weak.

Large changes in cosmic rays are documented in response to magnetic - field variations (the Laschamp event of about 40,000 years ago is especially prominent) with no corresponding change in climate, so any cosmic - ray influence on the climate must be very small (a weak correlation can be obscured by noise; a strong control is almost always visible «by eye,» and clearly is absent).

In some specific contexts, they may be even higher, but evidence there is very weak; i.e. the studies that do purport to show high numbers are typically conflate causality with correlation (see point two below).

While there are a few quant funds (Renaissance being most prominent) that evidently make a very good living exploiting minor price efficiencies, correlations etc, on balance the weak - form EMH has proved rather robust and is widely accepted as a reasonable approximation of reality.

Although some studies found small but significant positive correlations between GCR and high - and mid-altitude clouds (Laken et al., 2010; Rohs et al., 2010), these variations were very weak, and the results were highly sensitive to how the Forbush events were selected and composited (Laken et al., 2009).

The very sharp Doug Short at Adviser Perspectives, argues, for example, that «the correlation is fairly weak over the entire timeframe.»

Correlational analyses indicate that: there is a very weak negative correlation between turn - time and carrier's market share; turn - time is significantly negatively correlated with frequency; there is a very strong significant positive correlation between frequency and carrier market share.

Ten correlations were strong, 16 were moderate, 4 were weak, and 3 were very weak.

The majority (52.8 %) of correlations were moderate, 10 (27.8 %) were strong, 4 (11.1 %) were weak, and 3 (8.3 %) were very weak.