Assuming the line is not perfect, what are some sources of error?  If you state ‘human error’ be specific as to what the human did to cause error.

Human Anatomy & Physiology (11th Edition)
11th Edition
ISBN:9780134580999
Author:Elaine N. Marieb, Katja N. Hoehn
Publisher:Elaine N. Marieb, Katja N. Hoehn
Chapter1: The Human Body: An Orientation
Section: Chapter Questions
Problem 1RQ: The correct sequence of levels forming the structural hierarchy is A. (a) organ, organ system,...
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Assuming the line is not perfect, what are some sources of error?  If you state ‘human error’ be specific as to what the human did to cause error.

B
Standard Curve
0.7
y 0.0338**
R09145
0.6
0.5
04
203
0.2
0.1
10
15
20
25
Protein concentration (ug/ml)
Series1Series1
Linear (T-0)
Absorbano at 595 nm
Transcribed Image Text:B Standard Curve 0.7 y 0.0338** R09145 0.6 0.5 04 203 0.2 0.1 10 15 20 25 Protein concentration (ug/ml) Series1Series1 Linear (T-0) Absorbano at 595 nm
Expert Solution
Spectrophotometric analysis

With the help of Spectrophotometric analysis , we are able to calculate the concentration of a substance by measuring its absorbance value. Beer lamberts law tells us that Absorbance is directly proportional to the concentration of the analyte whose absorbance we measured. Hence a standard plot with Absorbance and Concentration of analyte as Y and X axis respectively can be obtained by measuring the absorbance of known concentrations of the analyte using spectrophotometer and then plotting the graph.

Once we plot the points , then we draw a best fit line i.e. a line that is the closest to all the points , this line is called the regression line (the blue dotted line in question) . Then we obtain the equation of the line which would be in the form ' y= mx +c'. Here 'y' is absorbance, 'm' is slope of the line, 'x' is concentration of analyte and 'c' is Y-intercept. We can calculate the concentration of the analyte in an unknown sample by simply measuring the absorbance value, substituting it as 'y' in equation and then solving for 'x' . 

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