Bicarbonate in replicate samples of horse blood was measured four times by each of two methods with the following results:

Method 1:31.40, 31.24, 31.18, 31.43 mM

Method 2:30.70, 29.49, 30.01, 30.15mM

(a) Find the mean, standard deviation, and standard uncertainty (= standard deviation of the mean) for each analysis.

(b) Are the standard deviations significantly different at the 95%confidence level?

Short Answer

Expert verified

a)The mean value for method 1 is x1¯=31.31mM.

The standard deviation value for method 1 is s1=0.12mM.

The standard uncertainty value for method 1 isu1=0.06.

The mean value for method 2 isx2¯=30.08mM.

The standard deviation value for method 2 is s2=0.49mM.

The standard uncertainty value for method 2 isu2=0.24.

b)The standard deviations are significantly different.

Step by step solution

01

Definition of standard deviation and mean.

  • Arithmetic mean:By dividing the amount of measured values by the number of measurements n, the arithmetic meanx¯ is determined. The average is often referred to as the "mean."

Mean:x¯=ixin

  • Standard deviation: The standard deviation is a measurement of how tightly the data cluster around the mean.

The standard deviation (s) is given by the formula:

s=ixi-x¯2n-1

Standard deviation of the mean of sets of n values is:

σn=θn

02

Find the meanstandard deviation, standard uncertainty.

(a)

Let x1¯, s1, and u1be the mean, standard deviation, and standard uncertainty of method 1.

Method 's mean, standard deviation, and standard uncertainty arex2¯,s2andu2respectively.

For Method 1 :

Mean:

localid="1663562989158" x1¯=ixin=31.40+31.24+31.18+31.434=31.31=31.312mMroundedoff

Therefore, the mean value for method 1 isx1¯=31.31mM

Standard deviation:

s1=i(xi-x2n-1=31.40-31.3122+.....31.43-31.31224-1=0.121=0.12mMroundedoff

Therefore, the standard deviation value for method 1 is s1=0.12mM.

Standard uncertainty:

role="math" localid="1663563250038" u1=s1n=0.121mM4=0.061=0.06roundedoff

Therefore, the standard uncertainty value for method 1 is u1=0.06

For Method2:

Mean:

x2¯=ixin=30.70+29.49+30.01+30.154=30.088=30.08mMroundedoff

Therefore, the mean value for method 2 is x2¯=30.08mM.

Standard deviation:

s2=i(xi-x)2n-1=30.70-30.0882+.....30.15-30.08824-1=0.497=0.49mMroundedoff

Therefore, the standard deviation value for method 2 is s2=0.49mM.

Standard uncertainty:

u2=nn=0.497mM4=0.249=0.24roundedoff

Therefore, the standard uncertainty value for method 2 is u2=0.24.

03

Find if the standard deviations significantly different at the $95 \%$ confidence level.

(b)

It must be determined whether the standard deviation differs considerably at the 95% confidence level.

Comparison of Standard Deviation with F Test:

We determine if the standard deviations of two sets of measurements are "statistically different" when comparing mean values. The Ftest is used to do this.

The Ftest with quotient F is given as:

Fcalculated=k12x22

Where, s1ands2 are standard deviations for the set of measurements using original instrument and substitute instrument.

The difference betweenFcalculated>Ftable is substantial.

IfFcalculated>Ftable, then there is a considerable difference..

Degrees of Freedom:

The degrees of freedom for aset of measurements will ben-1 .

The F-test is used to compare standard deviations, which is computed as follows:

Fcalculated=s12s22=0.49720.1212=16.8=16roundedoff

The Ftableis found as Ftable=9.28for three degrees of freedom in both standard deviations.

Fcomputed16>Ftable=9.28after comparing the two values.

As a result, the standard deviations varied dramatically.

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Most popular questions from this chapter

What fraction of vertical bars in Figure 4-5a is expected to include the population mean (10000) if many experiments are carried out? Why are the 90 % confidence interval bars longer than the 50 % bars in Figure 4-5?

Blood plasma proteins of patients with malignant breast tumors differ from proteins of healthy people in their solubility in the presence of various polymers. When the polymers dextran and poly(ethylene glycol) are mixed with water, a two-phase mixture is formed. When plasma proteins of tumor patients are added, the distribution of proteins between the two phases is different from that of plasma proteins of a healthy person. The distribution coefficient ( K) for any substance is defined as K =[concentration of the substance in phase[concentration of the substance in phase B ]. Proteins of healthy people have a mean distribution coefficient of 0.75 with a standard deviation of 0.07. For the proteins of people with cancer, the mean is 0.92 with a standard deviation of 0.11.

(a) Suppose that Kwere used as a diagnostic tool and that a positive indication of cancer is taken asK0.92. What fraction of people with tumors would have a false negative indication of cancer becauseK0.92?

(b) What fraction of healthy people would have a false positive indication of cancer? This number is the fraction of healthy people withK0.92, shown by the shaded area in the graph below. Estimate an answer with Table 4 - 1 and obtain a more exact result with the NORMDIST function in Excel.

(c) Vary the first argument of the NORMDIST function to select a distribution coefficient that would identify 75% of people with tumors. That is, 75% of patients with tumors would have K above the selected distribution coefficient. With this value of K, what fraction of healthy people would have a false positive result indicating they have a tumor?

(a) The linear calibration curve in Figure 4-13 isy=0.01630(±0.00022)x+0.0047(±0.0026)withsy=0.0059. Find the quantity of unknown protein that gives a measured absorbance of when a blank has an absorbance of 0.095

(b) Figure 4-13 has n=14 calibration points in the linear portion. You measure k=14replicate samples of unknown and find a mean corrected absorbance of 0.169 Find the standard uncertainty and 95%confidence interval for protein in the unknown.

Calibration curve. (You can do this exercise with your calculator, but it is more easily done by the spreadsheet in Figure.) In the Bradford protein determination, the color of a dye changes from brown to blue when it binds to protein. Absorbance of light is measured.

(a) Find the equation of the least-squares straight line through these points in the form y=[m(±um)]x+[b(±ub)]with a reasonable number of significant figures.

(b) Make a graph showing the experimental data and the calculated straight line.

(c) An unknown protein sample gave an absorbance of0.973. Calculate the number of micrograms of protein in the unknown and estimate its uncertainty.

Suppose that you carry out an analytical procedure to generate a linear calibration curve like that shown in Figure 4-13. Then you analyse an unknown and find an absorbance that gives a negative concentration for the analyte. What might this mean?

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