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To find \( P(H \geq 2) \), we need to sum the probabilities of the random variable \( H \) being 2 or 3 based on the given probability distribution:

\[
P(H \geq 2) = P(H = 2) + P(H = 3)
\]

From the table:
- \( P(H = 2) = 0.375 \)
- \( P(H = 3) = 0.125 \)

Adding these together:
\[
P(H \geq 2) = 0.375 + 0.125 = 0.5
\]

So, \( P(H \geq 2) = 0.5 \).

Do you have any further questions or need more details on this topic? Here are some related questions to consider:

1. How would you calculate \( P(H = 1 \text{ or } H = 2) \)?
2. Can you determine the expected value of \( H \) from this distribution?
3. How would you calculate the variance of \( H \)?
4. What is the probability that all three coins land on tails?
5. How do the concepts of mutually exclusive and independent events apply to flipping coins?

**Tip:** When calculating probabilities from a distribution table, ensure to correctly identify which events are included in your calculation and sum their probabilities accordingly.

Cora is playing a game that involves flipping three coins at once. Let the random variable H be the number of coins that land showing 'heads'. The probability distribution is given. Find P(H >= 2).

Learn how to calculate the probability P(H >= 2) for a coin-flipping game where three coins are tossed at once. This problem involves basic probability and summing probabilities from a given distribution table.

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