how to find expected value?
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In statistics and probability analysis, the expected value is calculated by multiplying each of the possible outcomes by the likelihood each outcome will occur and then summing all of those values. By calculating expected values, investors can choose the scenario most likely to give the desired outcome.
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['C = Future sum.', "i = Interest rate (where '1' is 100%)", 'n= number of periods.']
1323921
['50(. 15) = 7.5.', '76(. 20) = 15.2.', '80(. 20) = 16.', '98(. 45) = 44.1.']
986225
In statistics and probability analysis, the expected value is calculated by multiplying each of the possible outcomes by the likelihood each outcome will occur and then summing all of those values.
895497
['Probability = odds/1+ odds To go in the other direction from odds to probability:', 'Divide the odds by 1 + odds.', 'In this example, (1/4) / (1+1/4) =', '(1/4) / (5/4) =', '1/5, the probability.']
439740
It is calculated by multiplying potential outcomes by the chances of them occurring and then totaling these results. For example, if an investment has a 50% chance of gaining 20% and a 50% chance of losing 10%, the expected return is 5% (50% x 20% + 50% x -10% = 5%).
467906
['Earning Yield. Shares are valued on the basis of expected earning and the normal rate of return. Under this method, value per share is calculated using the below formula:', 'Dividend Yield. Under this method, shares are valued on the basis of expected dividend and the normal rate of return.']
323508
Like data, probability distributions have standard deviations. To calculate the standard deviation (σ) of a probability distribution, find each deviation from its expected value, square it, multiply it by its probability, add the products, and take the square root.
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['To calculate the expected return of a portfolio, you need to know the expected return and weight of each asset in a portfolio.', "The figure is found by multiplying each asset's weight with its expected return, and then adding up all those figures at the end."]
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Expected value shows us the value that is to be expected from engaging in a lottery (or risky situation) where there are 2 or more possible outcomes. Likewise, Expected utility shows us the utility that is expected out of a lottery with two or more possibilities.
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['Step 1: Find the mean.', 'Step 2: Subtract the mean from each score.', 'Step 3: Square each deviation.', 'Step 4: Add the squared deviations.', 'Step 5: Divide the sum by the number of scores.', 'Step 6: Take the square root of the result from Step 5.']
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Multiply the probability of each event times the expected losses. Referring to the Opportunity Loss table that you calculated above, multiply each of the predicted losses times the probability of that loss occurring. For example, the top row represents the low demand market, which has a probability of 0.4.
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['The mean value is calculated by adding all the data points and dividing by the number of data points.', 'The variance for each data point is calculated, first by subtracting the value of the data point from the mean. ... ', 'The square root of the variance—result from no.']
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['Subtract the original investment amount (or principal amount invested) from the current market value of the investment (or at the end of the investment period).', 'Take the result from the numerator and divide it by the original investment amount.']
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['Find P(Z > a). The probability that a standard normal random variable (z) is greater than a given value (a) is easy to find. The table shows the P(Z < a). ... ', 'Find P(a < Z < b). The probability that a standard normal random variables lies between two values is also easy to find.']
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['x <- c(1, 2, 3)', 'sqrt(mean(x ^ 2) - mean(x)^2)', '# [1] 0.8164966.']
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The expected value of the difference between all possible sample proportions is equal to the difference between population proportions. Thus, E(p1 - p2) = P1 - P2.