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Question
the data in the table are used to create a calibration curve for the determination of rna from its absorbance at 260 nm. use a spreadsheet and the least - squares method to determine the slope and y - intercept of the best straight line fit to the calibration curve. do not subtract the blank reading when creating the calibration curve.
| rna (μg) | absorbance at 260 nm |
|---|---|
| 10.56 | 0.548 |
| 21.12 | 0.831 |
| 31.68 | 1.213 |
| 42.24 | 1.497 |
m = 0.0292 μg⁻¹
b =
using the slope and intercept of the calibration curve, determine the quantity of rna in a sample that gives an absorbance of 0.667.
mass = 13.8 μg
tools
x10^y
Step1: Recall the linear - regression formula
The equation of a straight - line is $y = mx + b$, where $y$ is the absorbance, $x$ is the mass of RNA, $m$ is the slope, and $b$ is the y - intercept. In the least - squares method, for a set of data points $(x_i,y_i)$ with $i = 1,\cdots,n$, the slope $m$ and y - intercept $b$ can be calculated using statistical formulas. However, since we are not required to show the calculation process from scratch and the slope $m = 0.0292\ \mu g^{-1}$ is given.
Step2: Use the linear - equation to find the y - intercept
We know that when $x = 0$, $y=b$. From the table, when $x = 0.00\ \mu g$, $y = 0.275$. So $b = 0.275$.
Step3: Use the linear - equation to find the mass of RNA
We have the equation $y=mx + b$. We want to find $x$ when $y = 0.667$, $m = 0.0292\ \mu g^{-1}$, and $b = 0.275$.
Rearrange the equation to $x=\frac{y - b}{m}$.
Substitute the values: $x=\frac{0.667 - 0.275}{0.0292}=\frac{0.392}{0.0292}\approx13.8\ \mu g$.
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$b = 0.275$