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Statistics and Visuals


This handout explains how to write with statistics including quick tips, writing descriptive statistics, writing inferential statistics, and using visuals with statistics.

Contributors:Reuben Ternes
Last Edited: 2016-02-27 10:44:45


Don't be afraid to use graphics. Statistics can contain a lot of information. Visuals can display a lot of information in a manner that can be quickly understood. The same thing applies to tables. For example:

The mean (and standard deviation in parentheses) for group A was 10.5 (2.1), the mean (S.D.) for group B was 12.3 (1.2) the mean (S.D.) for group c was 15.9 (1.8), and the mean (S.D.) for group D was 21.3 (2.5).

It' s hard to read! Imagine trying to make sense of this. Instead, provide your data in a table for easy reading:

Group A Group B Group C Group D
Mean 10.5 12.3 15.9 21.3
S.D. 2.1 1.2 1.8 2.5

A table is much easier to read than blocks of text. It can help sort the information for both you and your readers. It also makes group comparisons easy. For example, suppose you want to point out to the reader the difference between group A and group D (perhaps this was a new weight training program comparing the number of 80 lbs. dumbbell reps).

Group A Group B Group C Group D
Mean 10.5 12.3 15.9 21.3
S.D. 2.1 1.2 1.8 2.5

Or, you could do this:

Group A Group B Group C Group D
Mean 10.5 * 12.3 15.9 21.3 *
S.D. 2.1 1.2 1.8 2.5

Don't be afraid to bold, use asterisks, or otherwise highlight important groups or comparisons.


Graphs are an excellent alternative to tables, and they are used by virtually everyone in every field. Papers and articles are like faces. Graphics are like makeup. Makeup is always good in small doses, but don't over apply, or you will end up looking worse than if you didn't use any make up at all. Use visuals, but be careful not to over use them. This is a good example of a visual using the data from the previous table:

Visual display of the tables presented earlier in the article—columns are displayed A-D.

Image Caption: Visual Graph of Data

Consider distributions of information for a moment. Imagine that we are teaching a class and displaying the students' first homework grades to the students for their benefit. This is one of the ways we could display their homework grades.

A graph with too much information - there are twenty small bars of color with no labels.

Image Caption: Poor example of a graph.

In this graph, each of these bars represents a student (each student gets a different color). This is an example of using too much make-up. While the graph does convey a lot of information, it is hard to read. The following graph is much better, and it actually gives you some useful information regarding the class:

Image that presents information in terms of percent of students who scored a 1-10, not by each student as above.

Image Caption: Better graph of student scores

Now we can clearly see that one person did really poorly, but that most people were clustered between 70-90%. In the first graph of student scores, we can't really 'see' the distribution, but in this second graph we have a much clearer image of the distribution of scores.

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