In an election, uppose that 50% of voters support the incumbent candidate. If we poll 115 of these voters at random, the probability distribution for the proportion of the polled voters that support the incumbent candidate can be modeled by the normal distribution pictured below.
In an election, uppose that 50% of voters support the incumbent candidate. If we poll 115 of these voters at random, the probability distribution for the proportion of the polled voters that support the incumbent candidate can be modeled by the normal distribution pictured below.
In an election, uppose that 50% of voters support the incumbent candidate. If we poll 115 of these voters at random, the probability distribution for the proportion of the polled voters that support the incumbent candidate can be modeled by the normal distribution pictured below.
In an election, uppose that 50% of voters support the incumbent candidate. If we poll 115 of these voters at random, the probability distribution for the proportion of the polled voters that support the incumbent candidate can be modeled by the normal distribution pictured below. Complete the boxes accurate to two decimal places.
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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