If you have a distribution with a very large range, but a small standard deviation, what does that tell you about your data set? the distribution is very flat with a gradual increase in frequency as the numbers approach the mean. there are most likely a few outliers, with the rest of the data close to the mean. you can't really know anything about the distribution's shape without actually seeing it, or having more data. the distribution is essentially normal or bell shaped.

There are most likely a few outliers, with the rest of the data close to the mean. The standard deviation is an indication of how "wide" the peak of the graph is. Since we have a very large range, that means that the values cover a very large range. But since the standard deviation is small, that means that most of the values are extremely close to the average (or mean) of the values. With that in mind, let's look at the options and see what fits. The distribution is very flat with a gradual increase in frequency as the numbers approach the mean. * This would have a rather large standard deviation since most of the values would be a fair distance from the mean. So this is a bad choice. There are most likely a few outliers, with the rest of the data close to the mean. * This is a very accurate description of the situation. So it's the correct choice. You can't really know anything about the distribution's shape without actually seeing it, or having more data. * This is a cop out and quite wrong. Therefore this is a bad choice. The distribution is essentially normal or bell shaped. * This is what is usually expected, but since we have a small standard deviation, the curve is more definitely NOT bell shaped. So this is a wrong choice.