It is 0.5
It is 0.3438
1/16
In a large enough number of tosses, it is a certainty (probability = 1). In only the first three tosses, it is (0.5)3 = 0.125
To determine the probability of obtaining 45 or fewer heads in 100 tosses of a fair coin, you can use the binomial distribution model. The number of trials (n) is 100, and the probability of success (getting heads) on each trial (p) is 0.5. The cumulative probability can be calculated using statistical software or a binomial probability table, yielding a result near 0.5, as 45 heads is close to the mean of 50 heads expected in 100 tosses. For precise calculations, employing the normal approximation to the binomial distribution can also provide an estimate.
With 5 coin tosses there are 32 possible outcomes. 10 of these have exactly 2 heads, and 26 of these have 2 or more heads.For exactly two coins are heads: 10/32 = 31.25%For two or more heads: 26/32 = 81.25%
The probability of tossing heads on all of the first six tosses of a fair coin is 0.56, or 0.015625. The probability of tossing heads on at least one of the first six tosses of a fair coin is 1 - 0.56, or 0.984375.
It is 0.3438
1/16
If the coin is fair, the probability of getting all heads will decrease exponentially towards 0.
In a large enough number of tosses, it is a certainty (probability = 1). In only the first three tosses, it is (0.5)3 = 0.125
It is 1/2.
130 instances of 3 heads out of 1024 total possible outcomes=130/1024=0.126953125
The probability of getting five heads out of 10 tosses is the same as the probablity of getting five tales out of ten tosses. One. It will happen. When this happens, you will get zero information. In other words, this is the expected result.
Yes. You are measuring the number of 'successes', x, (in this case the number of heads) out of a number of 'trials', n, (in this case coin tosses) that has an assumed probability, p, (in this case 50% expressed as 0.5) of happening. This phenomenon follows a binomial distribution. Apply the binomial distribution to evaluate whether the the probability of x success from n trials with probability p of occurring is within a pre-determined 'acceptable' limit. Let's say you observe 54 heads in 100 tosses and you wonder if the coin really is fair. From the binomial distribution, the probability of getting *exactly* 54 heads from 100 tosses (assuming that the coin *is* fair & should have 0.5 chance of landing on either side) is 0.0580 or 5.8%. Note that this is not the same probability as 54 heads *in a row*. Most statisticians would agree that 5.8% is too large and conclude that the coin is fair.
With 5 coin tosses there are 32 possible outcomes. 10 of these have exactly 2 heads, and 26 of these have 2 or more heads.For exactly two coins are heads: 10/32 = 31.25%For two or more heads: 26/32 = 81.25%
Since it is a fair coin, the probability is 0.5
If it is a fair coin, the probability is 1/4.If it is a fair coin, the probability is 1/4.If it is a fair coin, the probability is 1/4.If it is a fair coin, the probability is 1/4.