For a population the mean and the expected value are just two names for the same thing. For a sample the mean is the same as the average and no expected value exists.
You probably mean "average"- the "middle" or "expected" value of a data set.
The expected value of a Martingale system is the last observed value.
The expected value is 7.
Expected value is the outcome of confidence of how probability distribution is characterized. If the expected value is greater than the confidence interval then the results are significant.
The expected value is the average of a probability distribution. It is the value that can be expected to occur on the average, in the long run.
The expected value is the long-run average value of repetitions of the experiment it represents.
For a population the mean and the expected value are just two names for the same thing. For a sample the mean is the same as the average and no expected value exists.
average number of successes
You probably mean "average"- the "middle" or "expected" value of a data set.
No. The expected value is the mean!
The mean of a discrete probability distribution is also called the Expected Value.
The expected value of a Martingale system is the last observed value.
It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.
The expected value is 7.
Expected value is a measure of the average outcome of a decision, calculated by multiplying the probability of each possible outcome by the value of that outcome. In decision-making, the expected value helps to assess the potential outcomes of different choices based on their probabilities, allowing individuals to make informed decisions by considering both the likelihood of different outcomes and their associated values.
Expected value is the outcome of confidence of how probability distribution is characterized. If the expected value is greater than the confidence interval then the results are significant.