If you tossed a coin 10 times and found 8 heads, and you're given the prior p(0) = 20, is the probability of the coin coming up head. What is the MAP estimate of ? 0.8 9 11 2 11 O 0.2

MATLAB: An Introduction with Applications
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**Question:**

If you tossed a coin 10 times and found 8 heads, and you're given the prior \( p(\theta) = 2\theta \), \(\theta\) is the probability of the coin coming up head. What is the MAP estimate of \(\theta\)?

- ○ 0.8
- ○ \(\frac{9}{11}\)
- ○ \(\frac{2}{11}\)
- ○ 0.2

**Explanation:**

In this problem, you need to find the Maximum A Posteriori (MAP) estimate of \(\theta\), which is the probability of the coin landing on heads. Given the prior \( p(\theta) = 2\theta \), you will use Bayes' Theorem to calculate which value of \(\theta\) is most likely given the prior and the observed data (8 heads out of 10 tosses). The options provided for \(\theta\) are 0.8, \(\frac{9}{11}\), \(\frac{2}{11}\), and 0.2.
Transcribed Image Text:**Question:** If you tossed a coin 10 times and found 8 heads, and you're given the prior \( p(\theta) = 2\theta \), \(\theta\) is the probability of the coin coming up head. What is the MAP estimate of \(\theta\)? - ○ 0.8 - ○ \(\frac{9}{11}\) - ○ \(\frac{2}{11}\) - ○ 0.2 **Explanation:** In this problem, you need to find the Maximum A Posteriori (MAP) estimate of \(\theta\), which is the probability of the coin landing on heads. Given the prior \( p(\theta) = 2\theta \), you will use Bayes' Theorem to calculate which value of \(\theta\) is most likely given the prior and the observed data (8 heads out of 10 tosses). The options provided for \(\theta\) are 0.8, \(\frac{9}{11}\), \(\frac{2}{11}\), and 0.2.
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