Summary statistics for values on one variable

Applets: Summary Statistics - quantitative |||| Boxplot |||| Summary Statistics - categorical

Summary statistics - quantitative: Compute any of several summary statistics for the a set of quantitative values.

Understanding standard deviation:   (Will be putting together something from some of these  on the left, about half-way down)

Boxplot: Draw a boxplot of a set of quantitative values.

Summary statistics - categorical: Note that, to have a summary statistic of categorical data, one must have an entire set of numbers, as illustrated here. So we would usually call this a "summary table" of the data rather than a summary statistic.
You may choose to compute either the counts, proportions, or percentages of each of the possible categories for a categorical variable.
There are two reasons for this applet: (1) to see the data itself, since most reports will only show one of the summary tables here instead of the actual data and (2) to illustrate the different ways a summary table can be given.
Note that the count method has more information than the others, because you can find the total number of observations.

Cautions and clarifications:

• Quantitative variables: Quartiles are sometimes computed in slightly different ways, so different software packages may give slightly different answers. This applet computes the first quartile as the median of all the data values below the median and the third quartile as the median of the data values above the median.
• Boxplots and fences for outliers. These boxplots do identify suspected outliers individually with asterisks. Suspected outliers are identified as data values more than 1.5*IQR outside of the first and third quartiles.
• Categorical variables: You cannot reliably identify all the possible categories for a variable just by looking at a set of data from the variable. For instance, if one of the categorical variables measured on a person living in the US is "current address state" and your sample is only 100 people, then it is likely that some of the states will be missing from your data set. When you make a table or graph of a categorical variable, include all the possible values as categories, not just the ones you actually saw in your dataset, and, of course, list 0 for the count and 0% appropriately in your table or graph.

Information about entering data. All of these applets allow you to enter data.

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