Sentence examples for linear regression figure from inspiring English sources

The maximum and minimum observed unfolding temperatures of each molecular length are plotted and fitted by linear regression (Figure 8).

For the MLSEA, the D C /b relationship showed a distinct negative linear regression (Figure 6a), which implies increased accumulated stress and decreased earthquake clustering (Barton et al. 1999; Öncel and Wilson 2002).

Non-equilibrium conditions were obtained by including all data points in the linear regression (Figure 7). Figure 6 A Spearman correlation plot depicting the [ 18 F]FCho influx determined under equilibrium and non-equilibrium conditions.

Therefore, we calculated the annual mean of total ecosystem carbon with an error bar of standard deviation and performed a linear regression (Figure 6a), which shows the total ecosystem carbon increased steadily from 7,942 gC/m2 in 2006 to approximately 10,234 gC/m2 in 2050 (i.e., 28.9% increase), with a mean value of 9,056 gC/m2.

We also analyzed the dependence of the clinical trials, FDA approval, weighted degree and specific drug percentage values to the lethality values by linear regression (Figure S2, S6 and S7).

The time at which the frequency of a founder epitope first fell below 80% correlated significantly with the decline of the corresponding CTL responses from their peak (p = 0.001, linear regression; Figure 4C).

Therefore, we consider separately the effects due to long-term variations in time and influence of the solar cycle by applying a 2-D linear regression model (Figure 1b): Figure 1 Trend in the seasonal numbers of Moscow NLC nights.

Both axes were logged and a linear regression created (Figure 6). Figure 6 Transwell particulate deposition (μg/cm 2 ) at different smoke dilutions for a 30 minute whole smoke exposure.

The bias in the abundance within the EST database estimation of the expression level is approximately proportional to the gene length, as shown by the linear regression in Figure 4. Also shown in Figure 4 is the same length bias when the abundance is calculated from the full WormBase EST database [ 30, 31], rather than by the method that separates the data into two developmental stages [ 22].

On the other hand, stage II cannot be described by one kinetic equation, as the slopes obtained from the linear regression change (Figure 3b and Table 2).

No multicollinearity was present and the standardised residuals showed a normal distribution (Range = [ 2.92; 3.96]), meeting the important assumptions of normality and multicollinearity underlying multiple linear regression (see Figure S5, in Additional file 1).