Can one use the central limit theorem to find the probability of earning a certain amount of money when playing a card game twice if the probability distribution for possible earnings is not normally distributed
Can one use the central limit theorem to find the probability of earning a certain amount of money when playing a card game twice if the probability distribution for possible earnings is not normally distributed
Can one use the central limit theorem to find the probability of earning a certain amount of money when playing a card game twice if the probability distribution for possible earnings is not normally distributed
Can one use the central limit theorem to find the probability of earning a certain amount of money when playing a card game twice if the probability distribution for possible earnings is not normally distributed?
Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.
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