When was the last time you attended a presentation and fully understood every plot the presenter showed?

That has only happened to me when it was members of my group presenting projects I was deeply involved in. Why can’t I understand all the plots presented on projects I’m not involved in? Because I don’t know the data in advance and it’s rarely fully explained in the presentation.

I see the same two mistakes at nearly every presentation I attend. The most common mistake is neglecting to explain what the plot shows. I think this happens because the presenter is so familiar with the data that she/he thinks the plot doesn’t need an explanation. I have been guilty of this mistake myself.

But few in your audience is intimately familiar with your data—the rest needs an explanation.

When a presenter starts showing plots, a large part of the audience will start struggling to follow the presentation, and many may resort to daydreaming.

You don’t want that to happen; follow the steps below to avoid the two most common mistakes.

Mistake # 1: too little explanation

Many present a plot by saying something like: “As you can see here, group X have higher Y than group Z.” Then they move on. What is missing here? Go through the list below of things to remember, and the faults of the above sentence should become clear to you.

What you must remember to explain:

  1. How and why you obtained the data. The amount of detail depends on your audience.
  2. Explain the plot axes. You must remember to explain the measures on the x- and y-axis.
  3. Explain your data. If you have a bar plot, then what does each par represent? Even if you have 10 bars, you must explain them all. So only include the data that’s important for your presentation.
  4. Explain the results that the plot represents and what you conclude from it.

You don’t have to go through the steps in the order I wrote them above. The order depends on how you transition to talking about the plot. Sometimes, it may work best to start with the conclusion, and then explain the details of the plot. Before you move on, you can then repeat the conclusion.

Mistake # 2: unreadable font sizes

It’s a very common mistake to have labels in font sizes that are unreadable to the audience. Combine unreadable text with general forgetfulness to fully explain the plot, and you have a struggling audience.

Why is this mistake so common?

I believe it’s because most make their plots for publication and simply copy these into their slides. But plots made for publication have smaller fonts than a presentation requires.

The extra minutes it takes to make your labels readable are well spent. You want your message across, and you want a happy audience. Then ensure that they can read the information, you are asking them to read.

How large should the fonts be?

Some authors recommend between 24 and 28 pt as the smallest font sizes on slides. You can use this as a rule of thumb. But the best way to figure it out is to put your plot on a screen and ensure the text is legible from the back of the room.

Example

Here’s an example with fictional data. Let’s say you have found that growing cells in high phosphate concentration leads to larger cells. Now you are presenting the result.

 

Here’s how not to do it:

“As you can see here treating cells with high phosphate leads to larger cells”.

 

Here’s how to do it:

  1. Explain how and why you obtained the data (degree of detail depends on your audience).

“We hypothesized that if cells grow in high phosphate concentrations, they will become larger. To test this, I grew cells in 10 mM phosphate and control cells in 1 mM phosphate, which is the normal concentration in human blood. After six days I measured the diameter of the cells.”

 

  1. Explain the plot.

“The plot here shows the result. The x-axis shows the control group and the group treated with high phosphate. The y-axis shows the cell diameter in µM. The dots show the mean measure on cells from a single well”

 

  1. Explain the data and the result.

“The control cells had an average diameter of 11 µM, and the treated cells reached an average of 14 µM. The p-value obtained with a students t-test is 0.001. So we concluded that growing cells in high phosphate does result in larger cells.”

When you follow this approach, you may find that you spend more time explaining and that you can’t include as many plots as you usually do. Therefore, only include the information that is essential for your message or conclusion.

Keep it clear and simple. Don’t try to impress your audience with the amount of data you obtained or how much work you did.

Aim to inform and to have your audience understand and remember.

 

(Image: Pixabay.com)

 

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