Guidelines for Helping Your Audience Understand Statistics
- Use statistics as support, not as a main point. The audience may cringe or tune you out for saying, “Now I’d like to give you some statistics about the problem of gangs in our part of the state.” That sounds as exciting as reading the telephone book! Use the statistics to support an argument.
- Do not overuse statistics. While there is no hard and fast rule on how many to use, there are other good supporting materials, and you would not want to depend on statistics alone. You want to choose the statistics and numerical data that will strengthen your argument the most and drive your point home. Statistics can have emotional power as well as probative value if used sparingly.
- Use reputable sources for the statistics you present in your speech such as government websites, academic institutions and reputable research organizations and policy/research think tanks.
- Beware of unrepresentative samples. In an unrepresentative sample, a conclusion is based on surveys of people who do not represent, or resemble, the ones to whom the conclusion is being applied.
- Use a large enough sample size in your statistics to make sure that the statistics you are using are accurate (for example, if a survey only asked four people, then it is likely not representative of the population’s viewpoint).
- Use statistics that are easily understood. Many people understand what an average is but not many people will know more complex ideas such as variation and standard deviation.
- When presenting graphs, make sure that the key points are highlighted, and the graphs are not misleading as far as the values presented.
- Explain your statistics as needed, but do not make your speech a statistics lesson. If you say, “My blog has 500 subscribers” to a group of people who know little about blogs, that might sound impressive, but is it? You can also provide a story of an individual, and then tie the individual into the statistic. After telling a story of the daily struggles of a young mother with multiple sclerosis, you could follow up with “This is just one story in the 400,000 people who suffer from MS in the United States today, according to National MS Society.”
Common Misunderstandings of Statistics
A common misunderstanding when using statistics is “correlation does not mean causation.” This means that just because two variables are related, they do not necessarily mean that one variable causes the other variable to occur. For example, consider a data set that indicates that there is a relationship between ice cream purchases over seasons versus drowning deaths over seasons. The incorrect conclusion would be to say that the increase in ice cream consumption leads to more drowning deaths, or vice versa. Therefore, when using statistics in public speaking, a speaker should always be sure that they are presenting accurate information when discussing two variables that may be related. Statistics can be used persuasively in all manners of arguments and public speaking scenarios—the key is understanding and interpreting the given data and molding that interpretation towards a convincing statement.
Putting Statistics into Context for Our Audiences
Graphs, tables, and maps can be used to communicate the numbers, but then the numbers need to be put into context to make the message stick. As the Heaths state:
Statistics are rarely meaningful in and of themselves. Statistics will, and should, almost always be used to illustrate a relationship. It’s more important for people to remember the relationship than the number.
In their book, the Heaths give several good examples of others who have done this. For example, they introduce us to Geoff Ainscow, one of the leaders of the Beyond War movement in the 1980s.
Ainscow gave talks trying to raise awareness of the dangers of nuclear weapons. He wanted to show that the US and the USSR possessed weapons capable of destroying the earth several times over. But simply quoting figures of nuclear weapons stockpiles was not a way to make the message stick. So, after setting the scene, Ainscow would take a BB pellet and drop it into a steel bucket where it would make a loud noise. The pellet represented the bomb that was dropped on Hiroshima. Ainscow would then describe the devastation at Hiroshima. Next, he would take 10 pellets and drop them in the bucket where they made 10 times as much noise. They represented the nuclear firepower on a single nuclear submarine. Finally, he poured 5,000 pellets into the bucket, one for each nuclear warhead in the world. When the noise finally subsided, his audience sat in dead silence.
That is how you put statistics into context.
Using Tables, Graphs and Maps to Communicate Statistical Findings
The story of communicating your statistics does not end with putting them into context. Actually, it would be better to say that it does not begin with putting the numbers into context. In reality, the story you are telling through your evidence will probably start with the display of a table, graph, or map.
A simple table, graph, or map can explain a great deal, and so this type of direct evidence should be used where appropriate. However, if a particular part of your analysis represented by a table, graph, or map does not add to or support your argument, it should be left out.
While representing statistical information in tables, graphs, or maps can be highly effective, it is important to ensure that the information is not presented in a manner that can mislead the listener. The key to presenting effective tables, graphs, or maps is to ensure they are easy to understand and clearly linked to the message. Ensure that you provide all the necessary information required to understand what the data is showing. The table, graph, or map should be able to stand alone.
Tables, graphs, and maps should:
- relate directly to the argument;
- support statements made in the text;
- summarize relevant sections of the data analysis; and
- be clearly labelled.
Table Checklist
- Use a descriptive title for each table.
- Label every column.
- Provide a source if appropriate.
- Minimize memory load by removing unnecessary data and minimizing decimal places.
- Use clustering and patterns to highlight important relationships.
- Use white space to effect.
- Order data meaningfully (e.g., rank highest to lowest).
- Use a consistent format for each table.
Also, do not present too much data in tables. Large expanses of figures can be daunting for an audience, and can obscure your message.
Graph Checklist
- Title: Use a clear, descriptive title.
- Type of graph: Choose the appropriate graph for your message, avoid using 3D graphs as they can obscure information.
- Axes: Decide which variable goes on which axis, and what scale is most appropriate.
- Legend: If there is more than one data series displayed, always include a legend, preferably within the area of the graph.
- Labels: All relevant labels should be included.
- Color/shading: Colors can help differentiate; however, know what is appropriate for the medium you’re using.
- Data source: Provide the source of data you’ve used for the graph.
- Three-Quarters Rules: For readability, it’s considered best practice to make the y-axis three-quarters the size of the x-axis
Examples
Examples help the audience understand the key points; they should be to the point and complement the topic. Examples are essential to a presentation that is backed up with evidence, and it helps the audience effectively understand the message being presented. An example is a specific situation, problem, or story designed to help illustrate a principle, method or phenomenon. Examples are useful because they can help make an abstract idea more concrete for an audience by providing a specific case. Examples are most effective when they are used as a complement to a key point in the presentation and focus on the important topics of the presentation. An example must be quickly understandable—something the audience can pull out of their memory or experience quickly. There are three main types of examples: brief, extended, and hypothetical.
Brief Examples
Brief examples are used to further illustrate a point that may not be immediately obvious to all audience members but is not so complex that is requires a lengthier example. Brief examples can be used by the presenter as an aside or on its own. A presenter may use a brief example in a presentation on politics in explaining the Electoral College. Since many people are familiar with how the Electoral College works, the presenter may just mention that the Electoral College is based on population and a brief example of how it is used to determine an election. In this situation it would not be necessary for a presented to go into a lengthy explanation of the process of the Electoral College since many people are familiar with the process.
Extended Examples
Extended examples are used when a presenter is discussing a more complicated topic that they think their audience may be unfamiliar with. In an extended example a speaker may want to use a chart, graph, or other visual aid to help the audience understand the example. An instance in which an extended example could be used includes a presentation in which a speaker is explaining how the “time value of money” principle works in finance. Since this is a concept that people unfamiliar with finance may not immediately understand, a speaker will want to use an equation and other visual aids to further help the audience understand this principle. An extended example will likely take more time to explain than a brief example and will be about a more complex topic.
Hypothetical Examples
A hypothetical example is a fictional example that can be used when a speaker is explaining a complicated topic that makes the most sense when it is put into more realistic or relatable terms. For instance, if a presenter is discussing statistical probability, instead of explaining probability in terms of equations, it may make more sense for the presenter to make up a hypothetical example. This could be a story about a girl, Annie, picking 10 pieces of candy from a bag of 50 pieces of candy in which half are blue and half are red and then determining Annie’s probability of pulling out 10 total pieces of red candy. A hypothetical example helps the audience to better visualize a topic and relate to the point of the presentation more effectively.