From Łukasz Graczykowski
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| == Exercise == | | == Exercise == |
| Measurements of three physical observables <code>X1, X2</code> oraz <code>X3</code> have been made. Results of the measurements are in the following files: | | Measurements of three physical observables <code>X1, X2</code> oraz <code>X3</code> have been made. Results of the measurements are in the following files: |
- | [http://www.if.pw.edu.pl/~lgraczyk/wiki/images/e/ed/Dane1.dat Dane1.dat], [http://www.if.pw.edu.pl/~lgraczyk/wiki/images/0/0d/Dane2.dat Dane2.dat] oraz [http://www.if.pw.edu.pl/~lgraczyk/wiki/images/b/ba/Dane3.dat Dane3.dat]. | + | [http://www.if.pw.edu.pl/~lgraczyk/wiki/images/e/ed/Dane1.dat Dane1.dat], [http://www.if.pw.edu.pl/~lgraczyk/wiki/images/0/0d/Dane2.dat Dane2.dat] and [http://www.if.pw.edu.pl/~lgraczyk/wiki/images/b/ba/Dane3.dat Dane3.dat]. |
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| * Please calculate the result (mean and uncertainty - standard deviation) and draw the relation between the variables <code>(X1, X2)</code>, <code>(X2, X3)</code> and <code>(X1, X3)</code>. (1 pkt) | | * Please calculate the result (mean and uncertainty - standard deviation) and draw the relation between the variables <code>(X1, X2)</code>, <code>(X2, X3)</code> and <code>(X1, X3)</code>. (1 pkt) |
Latest revision as of 10:48, 28 March 2022
Exercise
Measurements of three physical observables X1, X2
oraz X3
have been made. Results of the measurements are in the following files:
Dane1.dat, Dane2.dat and Dane3.dat.
- Please calculate the result (mean and uncertainty - standard deviation) and draw the relation between the variables
(X1, X2)
, (X2, X3)
and (X1, X3)
. (1 pkt)
Variables Y1, Y2
are related to X1, X2, X3
via the following formulas:
Y1 = 2 X1 + 5 X2 + X3
Y2 = 3 + 0.5 X1 + 4 X2
Please calculate:
- covariance matrix X1, X2, X3 (1 pkt)
- mean values of Y1, Y2 in direct measurement (0.5 pkt)
- covariance matrix Y1, Y2 (1pkt)
- uncertainties of quantitites Y1, Y2 (1 pkt)
- correlation coefficients Y1 and Y2 (0.5 pkt)
Attention
- Look carefully three first slides from lecture 5 link
- Szczegółowy opis slajdy 12-16 from lecture 4 link
- Read data from file (the same as in C++):
ifstream ifile;
ifile.open("dane.dat");
double val;
while(ifile>>val)
{
cout<<val<<endl;
}
ifile.close();
- For all matrix operation (creating matrices of covariance, multiplication of matrices, transposing matrices) - use the class
TMatrixD
link
- Remember, that matrix operations require correct order of matrices.
- Uncertainty and correlation coefficient of X we obtain from TH2D histograms after reading the data; uncertainties and correlation coefficient of Y we obtain after calculating the matrix of coviarance of Y
- Limits of the histogram ranges in T2DH histograms in my solution are as follows:
double x1min = 1.5, x1max = 5.0;
double x2min = 0.0, x2max = 3.0;
double x3min = 4.0, x3max = 16.0;
TH2D *h12 = new TH2D("h12","Hist12",100,x1min,x1max,100,x2min,x2max);
TH2D *h13 = new TH2D("h13","Hist13",100,x1min,x1max,100,x3min,x3max);
TH2D *h23 = new TH2D("h13","Hist23",100,x2min,x2max,100,x3min,x3max);
Results
Plots:
Output:
X1=3.00691, u(X1)=0.495242
X2=2.00581, u(X1)=0.40909
X3=9.97287, u(X3)=1.98102
rho(X1,X2)=0.156132
rho(X1,X3)=-0.00698853
rho(X2,X3)=0.00875851
after rounding to 2 significant digits:
X1=3.01, u(X1)=0.50
X2=2.01, u(X1)=0.41
X3=9.97, u(X3)=1.98
This is the matrix of covariance for X
3x3 matrix is as follows
| 0 | 1 | 2 |
--------------------------------------------
0 | 0.2453 0.0316 -0.006855
1 | 0.0316 0.1674 0.0071
2 | -0.006855 0.0071 3.924
This is the matrix of covariance for Y
2x2 matrix is as follows
| 0 | 1 |
-------------------------------
0 | 9.765 3.949
1 | 3.949 2.865
Y1=26.0157, u(Y1)=3.1249
Y2=12.5267, u(Y2)=1.6927404
rho(Y1,Y2)=0.746574
rho(Y2,Y1)=0.746574
after rounding to 2 significant digits:
Y1=26.02, u(Y1)=3.13
Y2=12.53, u(Y2)=1.70