3. Activated-Protein-C (APC) resistance is a serum marker that has been associated with hrombosis (the formation of blood clots often leading to heart attacks) among adults. A dy assessed this risk factor among adolescents. To assess the reproducibility of the assay, lit-sample technique was used in which a blood sample was provided by 10 people; each ople was split into two aliquots (sub-samples), and each aliquot was assessed separately. TABLE 2.19 APC resistance spllt-samples data 1. To assess the reliability, compute the Standard Error of Mean Sample number А - В 2. To assess the variability of the assay, the investigators coefficient of variation. Compute the coefficient of variation (CV) for each subject by obtaining the standard deviation over the 2 replicates for each subject, and give your interpretation based on the evidence. need to compute the 1 2.22 1.88 0.34 3.42 3.59 -0.17 3.68 3.01 0.67 mean and 2.64 2.37 0.27 2.68 2.26 0.42 6 3.29 3.04 0.25 7 3.85 3.57 0.28 8. 2.24 2.29 -0.05 3.25 3.39 -0.14 10 3.30 3.16 0.14
3. Activated-Protein-C (APC) resistance is a serum marker that has been associated with hrombosis (the formation of blood clots often leading to heart attacks) among adults. A dy assessed this risk factor among adolescents. To assess the reproducibility of the assay, lit-sample technique was used in which a blood sample was provided by 10 people; each ople was split into two aliquots (sub-samples), and each aliquot was assessed separately. TABLE 2.19 APC resistance spllt-samples data 1. To assess the reliability, compute the Standard Error of Mean Sample number А - В 2. To assess the variability of the assay, the investigators coefficient of variation. Compute the coefficient of variation (CV) for each subject by obtaining the standard deviation over the 2 replicates for each subject, and give your interpretation based on the evidence. need to compute the 1 2.22 1.88 0.34 3.42 3.59 -0.17 3.68 3.01 0.67 mean and 2.64 2.37 0.27 2.68 2.26 0.42 6 3.29 3.04 0.25 7 3.85 3.57 0.28 8. 2.24 2.29 -0.05 3.25 3.39 -0.14 10 3.30 3.16 0.14
MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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
Transcribed Image Text:3. Activated-Protein-C (APC) resistance is a serum marker that has been associated with
hrombosis (the formation of blood clots often leading to heart attacks) among adults. A
dy assessed this risk factor among adolescents. To assess the reproducibility of the assay,
lit-sample technique was used in which a blood sample was provided by 10 people; each
ople was split into two aliquots (sub-samples), and each aliquot was assessed separately.
1. To assess the reliability, compute the
Standard Error of Mean
TABLE 2.19 APC resistance split-samples data
Sample number
A
А -В
2. To assess the variability of the assay, the
investigators need
coefficient of variation. Compute the
coefficient of variation (CV) for each
subject by obtaining the mean and
standard deviation over the 2 replicates for
each subject, and give your interpretation
based on the evidence.
1
2.22
1.88
0.34
to
compute the
3.42
3.59
-0.17
3
3.68
3.01
0.67
4
2.64
2.37
0.27
2.68
2.26
0.42
6.
3.29
3.04
0.25
7
3.85
3.57
0.28
8.
2.24
2.29
-0.05
9.
3.25
3.39
-0.14
10
3.30
3.16
0.14
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