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15 Barney has a biased coin. When the coin is thrown once, the probability that tho coin will land heads is 0.3 Bamey throws the coin 4 times. (a) Work out the probability that the coin will land heads exactly 3 times. (b) Work out the probability that the coin will lard heads at least once. (b) Coblity

Ask by Sanders Chen. in Egypt
Feb 03,2025

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(a) The probability of getting exactly 3 heads is 0.0756. (b) The probability of getting at least one head is 0.7599.

Solución

To solve the problem, we will use the binomial probability formula, which is given by: \[ P(X = k) = \binom{n}{k} p^k (1-p)^{n-k} \] where: - \( n \) is the number of trials (coin tosses), - \( k \) is the number of successful outcomes (heads), - \( p \) is the probability of success on a single trial, - \( \binom{n}{k} \) is the binomial coefficient, calculated as \( \frac{n!}{k!(n-k)!} \). ### Given: - Probability of heads, \( p = 0.3 \) - Probability of tails, \( 1 - p = 0.7 \) - Number of trials, \( n = 4 \) ### (a) Probability of getting exactly 3 heads We need to find \( P(X = 3) \): \[ P(X = 3) = \binom{4}{3} (0.3)^3 (0.7)^{4-3} \] Calculating the binomial coefficient: \[ \binom{4}{3} = \frac{4!}{3!(4-3)!} = \frac{4 \times 3!}{3! \times 1!} = 4 \] Now substituting into the formula: \[ P(X = 3) = 4 \times (0.3)^3 \times (0.7)^1 \] Calculating \( (0.3)^3 \) and \( (0.7)^1 \): \[ (0.3)^3 = 0.027 \] \[ (0.7)^1 = 0.7 \] Now substituting these values back: \[ P(X = 3) = 4 \times 0.027 \times 0.7 \] Calculating this: \[ P(X = 3) = 4 \times 0.0189 = 0.0756 \] ### (b) Probability of getting at least 1 head To find the probability of getting at least one head, we can use the complement rule: \[ P(\text{at least 1 head}) = 1 - P(\text{no heads}) \] First, we calculate \( P(X = 0) \): \[ P(X = 0) = \binom{4}{0} (0.3)^0 (0.7)^{4} \] Calculating the binomial coefficient: \[ \binom{4}{0} = 1 \] Now substituting into the formula: \[ P(X = 0) = 1 \times (0.3)^0 \times (0.7)^4 \] Calculating \( (0.7)^4 \): \[ (0.7)^4 = 0.2401 \] Thus, \[ P(X = 0) = 0.2401 \] Now, using the complement rule: \[ P(\text{at least 1 head}) = 1 - P(X = 0) = 1 - 0.2401 = 0.7599 \] ### Final Answers: (a) The probability that the coin will land heads exactly 3 times is \( 0.0756 \). (b) The probability that the coin will land heads at least once is \( 0.7599 \).

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Bonus Knowledge

To tackle the probability of getting heads when throwing a biased coin, let's dive into some fun facts! Did you know that the concept of probability dates back to ancient civilizations? The earliest recorded attempts at understanding probability were made by gambling enthusiasts in the 16th century, who calculated odds for games of chance and laid the groundwork for modern probability theory! Now, let’s talk about how to apply this to real-world scenarios! Understanding the probabilities of events can help in making decisions under uncertainty, like predicting weather patterns or the chances of rain. For example, if you know there's a 30% chance of heads from your biased coin, you can determine whether it's worth carrying an umbrella based on your next “coin toss”!

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