The cholesterol levels of adult American women has a mound-shaped and symmetric distribution

with a mean of 188mg/dL and a standard deviation of 24 mg/dL. In what interval would you expect most
American women’s cholesterol levels to be? Explain.

visit this web site and specify 0.50 for the area. It will give you the min/max values.

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To determine the interval in which we would expect most American women's cholesterol levels to be, we can use the concept of the normal distribution. The given information states that the cholesterol levels of adult American women form a mound-shaped and symmetric distribution, which is a characteristic of a normal distribution.

A normal distribution is often represented using a bell-shaped curve. In this case, the mean cholesterol level is 188 mg/dL, and the standard deviation is 24 mg/dL. The mean represents the center of the distribution, and the standard deviation measures how spread out the data points are from the mean.

To determine the interval in which we would expect most American women's cholesterol levels to fall, we can use a rule of thumb known as the empirical rule, or the 68-95-99.7 rule. According to this rule:

- Approximately 68% of the data falls within one standard deviation of the mean.
- Approximately 95% of the data falls within two standard deviations of the mean.
- Approximately 99.7% of the data falls within three standard deviations of the mean.

Based on the given information, we can calculate the interval within one standard deviation of the mean. The lower bound of this interval is the mean minus one standard deviation, and the upper bound is the mean plus one standard deviation.

Lower bound = 188 - (1 * 24) = 164 mg/dL
Upper bound = 188 + (1 * 24) = 212 mg/dL

Thus, we would expect approximately 68% of American women's cholesterol levels to fall within the interval of 164 mg/dL to 212 mg/dL.

It's important to note that this is an approximation based on the empirical rule, and the actual distribution of cholesterol levels may deviate slightly from a perfect normal distribution. However, in practice, many real-world distributions can be reasonably approximated by a normal distribution.