Find definitions and interpretation guidance for every statistic that is provided with the dotplot.

The sample size (N) is the number of nonmissing observations for a Y variable or a group.

The mean is the average of the data, which is the sum of all the observations divided by the number of observations.

For example, the wait times (in minutes) of five customers in a bank are: 3, 2, 4, 1, and 2. The mean waiting time is calculated as follows:
On average, a customer waits 2.4 minutes for service at the bank.

Use the mean to describe the sample with a single value that represents the center of the data. Many statistical analyses use the mean as a standard measure of the center of the distribution of the data.

The standard deviation is the most common measure of dispersion, or how spread out the data are about the mean.

For a normal distribution, approximately 68% of the values fall within one standard deviation of the mean, 95% of the values fall within two standard deviations, and 99.7% of the values fall within three standard deviations.

The minimum is the smallest data value.

In these data, the minimum is 7.

13 | 17 | 18 | 19 | 12 | 10 | 7 |
9 | 14 |

Use the minimum to identify a possible outlier or a data-entry error. One of the simplest ways to assess the spread of your data is to compare the minimum and maximum. If the minimum value is very low, even when you consider the center, the spread, and the shape of the data, investigate the cause of the extreme value.

The maximum is the largest data value.

In these data, the maximum is 19.

13 | 17 | 18 | 19 |
12 | 10 | 7 | 9 | 14 |

Use the maximum to identify a possible outlier or a data-entry error. One of the simplest ways to assess the spread of your data is to compare the minimum and maximum. If the maximum value is very high, even when you consider the center, the spread, and the shape of the data, investigate the cause of the extreme value.