Sentence examples for linear regression data from inspiring English sources

Linear regression data for respective calibration curves showed a good linearity for all pyrethroids with r = 0.991-0.996.

Table 2 Linear regression data for calibration plot ( n  = 3) Parameters Observations Linearity range 0.5 to 500 (μg/mL) Regression equation y = 100,017x − 319,621 Correlation coefficient 0.9989 Slope ± SD 100,017 ± 999.8 Intercept ± SD 319,621 ± 3,339.8 y, peak area; x, concentration of standard (μg/mL).

The linear regression data for the calibration curves (n = 6) showed a good linearity r = 0.9990 ± 0.0004, (Slope = 5.841 ± 0.755, Intercept = 1420.3 ± 36.4) over the concentration range of 200 1200 ng/spot with respect to peak area.

Table 1 Linear regression data and validation parameters of prednisolone acetate (1) and chloramphenicol (2).

The linear regression data and the method validation results are summarized in Table 3.

Table?2 displays the linear regression data for the calibration curve of eugenol.

The results from analyses of the regressions where the organochlorine levels were dichotomized into categories of ≥75th percentile and < 75th percentile of exposure were consistent with the results from the multivariate linear regressions (data not shown).

Uptake values were analyzed for simple Michaelis-Menten kinetics using a non-linear regression data analysis using GraphPad Prism 4 (San Diego, CA).

The line of best fit to the mean data was fitted using linear regression (the data files are available as md_arrhenius_crambin_averaged.sav, md_arrhenius_crambin_averaged.spv).spv

Linear regression of data excluding artifacts resulted in a scaling factor of 1.06 for LBM MR-AC).

The linear regression analysis data showed a good linear relationship (r 2 = 0.9989 ± 0.0010) for 6-gingerol in the concentration range of 0.5 μg to 500 μg/mL.