Beer's law scatter plot and trendline
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Beer's law scatter plot and trendline (linear regression)
A calibration curve or standard curve is usually using
series of standard solutions known concentrations is
prepared and measured using spectrophometer instrument
to determine the unknown concentration of sample.
It is represent a graph where concentration is plotted
against absorbance then a straight line (Beer's Law) is
fit to the data that you obtained and the resulting
equation is used to convert absorbance of the unknown
sample into concentration. This equation of this line by
first finding the slop (m= y2 - y1/x2 - x1) and changing
y = mx + c
For this experiment, the slope
and intercept of that line provide a relationship
between absorbance and concentration that determined by
Lambert-Beer Law is used to determine concentration [M,
from Absorbance [No unit], if the molar extinction
[M-1cm-1] of a compound and the path length of the
cuvette [cm] that the distance light passes through the
solution are known. The formula
of this relationship:
e * l * c
thus, the concentration can be calculated by: c=A/e
According the Lambert-Beer law, an increase in the
concentration of a solution leads to a increase in the
absorbance as linear.
Wikipedia Molar absorptivity
Wikipedia Lambert Law.
To plot any data in excel, you should enter the data, create a
scatter plot with only Markers
from data, and then add linear regression (trendline)
to make Excel the better line fit to the data and can be used as formula (y=mx+c)to calculate the concentration of
unknown compound. You can find the steps for how to plot data using
Excel 2007 in "MS Excel/How to draw the
graphical relation between two variables section".
The linear equation on chart represents the relationship between
Concentration (x) and Absorbance (y) for the compound.
To add linear regression line on your scatter
plot, right click on the data points, and then click add "trendline".
Choose "linear" as the type of Trend/Regression. Select check boxes of
"Display Equation on chart" and "Display R-squared value on chart", and
then click "OK".
The R-squared value gives the square of the
Pearson correlation coefficient of the linear regression. The closer
value of R to 1 means relationship between x and y is very exactly and
line fit to data.
xls file attachment
for this tutorial.
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