SUMMARY
The probability challenge presented involves a biased coin that has a $\frac{2}{3}$ chance of matching the previous flip and a $\frac{1}{3}$ chance of showing the opposite side. After the initial flip resulting in heads, the probability that the last of 2010 subsequent flips is also heads is calculated using a Markov chain approach. The transition matrix for this problem is defined as $\displaystyle A = \left | \begin{matrix} \frac{2}{3} & \frac{1}{3} \\ \frac{1}{3} & \frac{2}{3} \end{matrix} \right |$. The final probability is expressed as $P = \frac{1 + 3^{-2010}}{2}$, which approaches $\frac{1}{2}$ as n increases.
PREREQUISITES
- Understanding of Markov chains
- Familiarity with transition matrices
- Knowledge of difference equations
- Basic probability theory
NEXT STEPS
- Study Markov chain applications in probability theory
- Learn about transition matrix calculations and their implications
- Explore difference equations and their solutions
- Investigate the convergence of probabilities in stochastic processes
USEFUL FOR
Mathematicians, statisticians, and students studying probability theory, particularly those interested in Markov processes and their applications in real-world scenarios.