A dataset was collected consisting of eight ELISA absorbance readings, each corresponding to a different, increasing concentration of a substrate. The primary focus of the analysis is to characterize the relationship between substrate concentration and measured absorbance, facilitating calibration or interpretation of ELISA response as a function of substrate level.
Format
A data frame with 3 variables: DUnit, Concentration, Absorbance.
- DUnit
Factor. Unique identifier for each ELISA reading.
- Concentration
Numeric. Substrate concentration used for each reading.
- Absorbance
Numeric. ELISA absorbance value measured at the given substrate concentration.
Source
Welham, S. J., Gezan, S. A., Clark, S. J., and Mead, A. (2015) Statistical Methods in Biology: Design and analysis of experiments and regression
Examples
summary(lm(Absorbance ~ log10(Concentration + 1), data = elisa))
#>
#> Call:
#> lm(formula = Absorbance ~ log10(Concentration + 1), data = elisa)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -0.44580 -0.19811 0.04437 0.23182 0.34391
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 0.5458 0.1939 2.815 0.030571 *
#> log10(Concentration + 1) 1.5284 0.2324 6.575 0.000593 ***
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 0.3272 on 6 degrees of freedom
#> Multiple R-squared: 0.8781, Adjusted R-squared: 0.8578
#> F-statistic: 43.24 on 1 and 6 DF, p-value: 0.0005934
#>