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A biased coin is a coin that does not have an equal probability of landing on each side when flipped. For example, it may have a higher likelihood of landing on heads than tails due to an uneven weight distribution or design. This bias can be quantified, typically expressed as a percentage, indicating the probability of each outcome (e.g., a 70% chance of heads and a 30% chance of tails). Consequently, repeated flips of a biased coin will yield outcomes that reflect this skewed probability rather than the expected 50/50 results of a fair coin.

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1mo ago

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A coin is flipped 60 times it lands on heads 36 times Do you think that the coin is biased?

yes the coin is biased because it turned to heads 36 times.


How do you find probability of a biased coin when P of getting head is .6?

The probability of heads is 0.6 and that of tails is 0.4. Since the probabilities are not 0.5, it is a biased coin. That is the answer!


If I were to flip a coin 4 times. What is the probability of me getting heads twice?

If the coin is not biased, the answer is 0.375


What is a biased coin in probability?

Probability of getting a head or tail is not equal


How do you find the probability on a biased coin of getting 3 heads out of 3 coin tosses when the probability of getting a head is 60 percent?

0.63 = 0.216


Who is the fairest coin dealers?

I may be biased, but I vote for ME. Any coin dealer who is a member of PNG or ANA has pledged to deal honestly and if complaints are filed against him he will be disciplined or lose his membership.


A coin was flipped 60 times and came up heads 38 times At the 10 level of significance is the coin biased toward heads?

Possibly not - the sample of 60 times is very small.


Why silicon controlled rectifier doesn't work in reverse biased condition?

Because when reverse biased it behaves like any other rectifier/diode.


What is a biased coin probability?

A biased probability is one where not every outcome has the same chance of occurring. A biased coin is one where one side, the "heads" or "tails" has a greater probability than the other of showing. A coin which has a centre of gravity closer to the tails side than the heads side would be biased in that heads is more likely to show than tails. The size of coin can have an effect on the probability of heads and tails - during the Royal Institute Christmas lectures in the 1990s demonstrating probability a large version of the pound coin was made to be able to allow the audience to see it being tossed - on the broadcast (and tape) version it landed and stayed on its edge! showing the probability of heads = tails ≠ ½; the probability of heads = probability of tails, but they are actually slightly less than ½ as the coin could land on its edge and stay there - with a standard size coin, if it lands on its edge it takes very little for the centre of gravity to shift outside the base of the edge and for the coin to fall over, but with a very large similar coin (ie one scaled up [proportionally] in lengths) it can take quite a bit before the centre of gravity goes outside the base if it lands on its edge which forces it to fall over (plus there will be a "significant" rise in the centre of gravity to do so, thus favouring stability on an edge which does not exist in the standard, small, sized version of the coin).


How do you make a percent for this problem miki tosses a coin 50 times and the coin shows head 28 times What is the percent?

28 times out of 50 as a percent is achieved thus (28/50)*100 = 56% (The coin would appear to be biased by the way).


What is biased in math?

I'm guessing this is a probability question. A die (or coin, or spinner, or roulette wheel, or other method of choosing something randomly) is fair if each possibility (1,2,3,4,5,6) has an equal chance of coming up. Anything that isn't fair is biased. For example a die that has been weighted to make 6s come up is biased.


If you obtained 170 heads would you think that the coin was biased?

If I obtained 170 heads out of a large number of coin flips (say 300 or more), I would likely suspect that the coin might be biased. In a fair coin, the expected proportion of heads would be around 50%, so getting 170 heads would be significantly higher than expected. However, I would also consider the total number of flips and perform statistical tests, such as a chi-squared test, to determine if the deviation from the expected outcome is statistically significant.