According to the range rule of thumb, the standard deviation of a data set can be roughly estimated as $\frac{\mathrm{Range}}{4}$.

An observation is considered an outlier if it is below which of the following values in a normal distribution?

According to the range rule of thumb, the standard deviation of a data set can be roughly estimated as which of the following expressions?

Which term represents the number of standard deviations an observation is from the $\mathrm{mean}$?

For a bell-shaped data set, approximately what percentage of the data will be in the interval $\mu -\sigma$ to $\mu +\sigma$?

If a set of data has a standard deviation of $0$, which of the following must be true about the data?

As the mean $\mu$ increases in a normal distribution, what happens to the graph of the normal curve?

Which of the following is not a property of the $standarddeviation$?

Suppose you have two histograms, A and B, each representing the distribution of exam scores for two different classes. Histogram $A$ shows scores tightly clustered around the mean, while Histogram $B$ shows scores spread out over a wider range. Which histogram depicts a higher $\mathrm{standard} \mathrm{deviation}$?