Updated README.md to identify whichs script to run

Author: oleksandr-pavlyk

examples/README.md

@@ -17,10 +17,40 @@ This data is post-processed as necessary for the application.
 Code is tested to estimate the probability that 3 segments, obtained by splitting a unit stick 
 in two randomly chosen places, can be sides of a triangle. This probability is known in closed form to be $\frac{1}{4}$.
 
+Run python script "stick_triangle.py" to estimate this probability using parallel Monte-Carlo algorithm:
+
+```
+> python stick_triangle.py
+Parallel Monte-Carlo estimation of stick triangle probability
+Parameters: n_workers=12, batch_size=262144, n_batches=10000, seed=77777
+
+Monte-Carlo estimate of probability: 0.250000
+Population estimate of the estimator's standard deviation: 0.000834
+Expected standard deviation of the estimator: 0.000846
+Execution time: 64.043 seconds
+
+```
+
 ## Stick tetrahedron problem
 
 Code is used to estimate the probability that 6 segments, obtained by splitting a unit stick in 
 5 random chosen places, can be sides of a tetrahedron. 
 
 The probability is not known in closed form. See
-[math.stackexchange.com/questions/351913](https://math.stackexchange.com/questions/351913/probability-that-a-stick-randomly-broken-in-five-places-can-form-a-tetrahedron) for more details.
+[math.stackexchange.com/questions/351913](https://math.stackexchange.com/questions/351913/probability-that-a-stick-randomly-broken-in-five-places-can-form-a-tetrahedron) for more details.
+
+```
+> python stick_tetrahedron.py -s 1274 -p 4 -n 8096
+Parallel Monte-Carlo estimation of stick tetrahedron probability
+Input parameters: -s 1274 -b 65536 -n 8096 -p 4 -d 0
+
+Monte-Carlo estimate of probability: 0.01257113
+Population estimate of the estimator's standard deviation: 0.00000488
+Expected standard deviation of the estimator: 0.00000484
+Total MC size: 530579456
+
+Bayesian posterior beta distribution parameters: (6669984, 523909472)
+
+Execution time: 30.697 seconds
+
+```