the distribution of household income in the United States is not believed to be normally distributed but is instead right-skewed. Suppose that the mean income of US households is $92,300 with a standard deviation of $32,000.
(e) Why is the standard deviation of the mean income in the sample of 100 households that you computed in part (d) much lower than the population standard deviation of $32,000? -- (part (d) is suppose 100 households are randomly selected and the average income is calculated. what is the standard dev of the mean income in the sample of 100 households - I got 3200 for that.)
(f) Suppose 100 households are randomly selected and the average income in the sample is calculated. Based on the Central Limit Theorem, what is the approximate probability that the mean income in the sample of 100 households is less than $89,000?
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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