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To determine if the coin can be considered fair, we need to analyze the probability of observing such an outcome (8 tails and 2 heads) under the assumption that the coin is fair. A fair coin implies that the probability of getting heads (p) is 0.5 and the probability of getting tails (1-p) is also 0.5.
The binomial distribution models the number of successes in a fixed number of independent Bernoulli trials, each with the same probability of success. In this context:
The probability of getting exactly x successes in n trials is given by the formula:
P(X=x)=(xn)px(1−p)n−x
Where:
For the given scenario (8 tails and 2 heads):
Plug these values into the formula:
P(X=2)=(210)(0.5)2(1−0.5)10−2
Calculate the binomial coefficient:
(210)=2×110×9=45
Now calculate the probability:
P(X=2)=45×(0.5)2×(0.5)8=45×(0.5)10=45×0.0009765625≈0.0439
To determine if the coin is fair, we compare the calculated probability (0.0439) with a significance level, typically 0.05. Since 0.0439 < 0.05, this result is statistically significant, suggesting that such an extreme outcome (8 tails and 2 heads) is unlikely under the assumption of a fair coin.
Given the low probability under the fair coin assumption, we might consider alternative hypotheses such as:
Conducting further tests or experiments with a larger sample size can provide more robust conclusions.
Based on the statistical analysis, the observed outcome of 8 tails and 2 heads is unlikely to occur with a fair coin. While this suggests potential bias, further testing with a larger number of trials is recommended to make a definitive conclusion.