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What is a statistical poster?

It is a one-page presentation that tells a story about a set of data.
It should:

  • be simple and have a logical progression (contain a goal, an approach, main findings and key conclusions)
  • include graphs and descriptive summaries of data
  • contain commentary on the meaning of the data
  • be self-contained (viewers should not need any extra material or information to understand the poster)
  • be visually attractive and creative

1. Plan/Decide on research question
2. Collect or use existing data
3. Analyse the data
5. Make the poster/ Present your findings


The starting point for any statistical poster is deciding on your research question. What is it exactly that you want to study/analyse and present to your audience? You need to formulate a question that can be answered with data – that is the essence of statistical research. Try to choose a topic that you are genuinely interested in. You are going to be working on this topic for weeks/months while you research, analyse and present your findings, so choose something that will hold your interest and that you can get excited about. Your attitude towards your research will come across in your writing and presentation! Maybe organise a brainstorming session with some of your classmates to come up with some ideas. You must ensure that the topic that you select is manageable and that you will be able to access data to support your research. It’s much better to pick a simple topic and present your findings clearly rather than to pick a complex topic which is difficult to explain. Past winners of the competition have been across a broad range of themes, from sport, social media, environment etc. The common denominator was that the students had picked an interesting topic and presented their findings in a clear and engaging manner.
Once you have settled on your research topic, do some background reading around it to familiarise yourself with the subject matter. This will help you with the next stages of the process.
An important factor to bear in mind at the planning stage is that you must decide on who or what your target population is for the research project. How will you access your target population? If your target population is your class, then you can access them quite easily, but if your target population is broader than that, then you will probably need to select a sample from the population. These are all issues that you should consider at the planning stage of your study.


In the majority of statistical research projects, the next step involves some element of data collection. You want to use this data to inform your decisions regarding the theory or hypothesis that you are investigating. Consider the method that you will use to collect the data and decide if this will work for your particular target population. If you have decided to select a sample for your study, consider how the sample will be selected so that it will be representative of the population.

Data can be collected through numerous methods; you can collect data through observation where you observe and record behaviour and characteristics of people, objects, or phenomena; you can conduct interviews with your study participants; you can design and issue questionnaires to your sample. Or maybe you can use secondary data for your study? Secondary data is data that has already been collected and is made available to researchers. The CSO website provides links to a vast selection of databases and data sources covering many topics ( Try to choose a collection method that will yield the most relevant and accurate data possible.
Studies that use statistics to answer questions require you to collect data in the form of variables that you’ll analyse. Consequently, you must define the variables that you will measure and decide how you’ll measure them. If you do not collect the correct data or if you measure it inaccurately, you might not be able to answer your research question. Take your time determining which variables you’ll need to measure to answer your research question.


Once you have collected the data, you must find a way of turning it into information. Raw data on its own isn’t particularly useful. You need to organise, structure and analyse the data in a way that will allow you to answer the questions posed in your original research question.
The first step should always be to clean your data, i.e. make sure that there aren’t any mistakes such as typos, duplicates etc. If you have collected some data as text strings, you might want to consider developing a coding system to convert the text into numeric codes to make it easier to analyse.
It’s always a good idea to start out with some exploratory data analysis in order to develop an understanding of your data and to summarise the main characteristics. Start exploring it by creating some graphs. When you’re dealing with large volumes of data, visualisation is the best way to explore and communicate your findings. How you visualise the distribution of a variable will depend on whether the variable is categorical or continuous. A variable is categorical if it can only take one of a small set of values (e.g. eye colour) and a variable is continuous if it can take any of an infinite set of ordered values (e.g. height). Bar charts are a useful way of examining categorical variables and histograms are good for looking at continuous variables. You can use these graphs to ask yourself questions like:

  • Which values are the most common? Why?
  • Which values are rare? Why? Does that match your expectations?
  • Can you see any unusual patterns? What might explain them?

As well as helping you to understand your data better, these questions will also allow you to identify possible errors or inconsistencies in your data.
You should also try to summarise your data numerically. When you want to summarise data, it’s always good to look at the following four aspects:

• Centrality – the middle value or average
• Dispersion – how spread out the values are from the average
• Size – how large your sample is
• Shape – the data distribution, which relates to how “evenly” the values are spread either side of the average

There are different measure of centrality and dispersion, so you need to choose the ones that are best suited to your particular data.
If the purpose of your study is to draw conclusions beyond the data that you have analysed, or to reach conclusions about some hypotheses, then you will need to do more than just describe and summarise your data. You will have to carry out some statistical tests to inform your decisions. In choosing the type of analysis to perform, you need to understand the types of data that you have (i.e. categorical or continuous, whether it is normally distributed or not etc.) There are lots of online resources that will point you to the correct test for your circumstances.

Present your findings

When you have completed the analysis stage of your project, it’s time to pull all of the information together and present it to your audience. The challenge with a statistical poster competition is to be able to showcase your project in a clear, engaging, and visually attractive way that will hold the reader’s attention. No mean feat! When you’re putting your poster together, try to put yourself in the position of a reader that has no knowledge of the subject matter. This will help you to make sure that you have presented all of the information that is required to understand both the background to your study, and the conclusions that you have drawn.
You will have to be concise in your presentation style as there are limits to the size of your poster. This means that you will have to strike a balance between giving enough information to get your points across and not overfilling the space on the poster making it look cramped. We all know the saying that “a picture paints a thousand words” so using graphs in your presentation will help you to convey your message concisely.
It’s important to consider the graph/graphic you are using in your presentation. For example, if you’re collecting data over time, a line graph might be the best option but if you’re showing how the results of a survey are distributed then a histogram might be the way to go. It’s always worth doing a bit of research into the best way to represent your data and results.
Infographics are another valuable tool for visual communication, and this makes them ideal for use in statistical posters. Infographics are visual representations of information or data. A good infographic will instantly grab your attention and help us understand a concept. There are lots of online resources where you can download ready-made infographics, and some where you can design your own.
As well as using visual aids, you will need to discuss and interpret your findings in the context of your original research question. Give your interpretation of how the data answers your original questions. What conclusions can be drawn, and will those conclusions extend to the entire population? Analyse the strengths and weaknesses of your study. Are there things that you learned along the way that would lead you to carry out the study in a different way if you were to do it again?

Making the poster

The poster must be in electronic format only
Posters should be:

  • An online one-page poster presentation (oriented either vertically or horizontally) i.e. multiple page presentations are not acceptable. No paper poster entries are accepted, or photographs of paper entries. This is a digital, online poster competition
  • Acceptable file formats include PNG, JPEG, GIF and PDF format only
  • Maximum poster file size is 1MB
  • The poster should be readable from a distance of two metres (seven feet) when printed on an A1 sized sheet
  • The poster should have no identifying information on it i.e. student names or school names


Posters should contain:

  • what was studied and how.
  • the main results, discussion about results and the principal conclusions.
  • be presented using pictures and key graphs.
  • have simple text telling the story of the data.
  • include summaries but not all the raw data.

Remember that there is only limited space so do not say things twice.
Pick only the graphs that best present the results. All graphs should be titled and commented on.
Try to avoid using a dark background colour in your poster as it can make some of the text very difficult to read. Sometimes colours and fonts can look different on screen and on paper, so it might be a good idea to print a copy of your poster to see how it looks before you submit it. Also, consider the balance of blank space versus text/graphs; while a certain amount of blank space is needed in the margins etc. so that the poster is not too cluttered, small font sizes and small graphs are difficult to read.
Think about the appropriateness of the graphs that you use. Bar charts are good for comparisons, while line charts work better for trends. Scatter plot charts are good for relationships and distributions, but pie charts should be used only for simple compositions — never for comparisons or distributions. Graphs should help the reader to understand your results so be sure to label your axes and use a legend if required.
Finally, make sure to proof-read your poster before you submit it as typos and spelling mistakes can take from the overall impression of a poster.
Try not to over-complicate your poster by attempting to test or analyse too many things.
If survey data comes from a particular school, some background on the school should be provided so that the context of the findings may be more transparent.
The possible effects of non-response could be explored.
Exercise caution when reporting your findings. Avoid overstating the inferences/conclusions that can be made from the results – usually the inferences are limited to the sample and probably can’t be extended to the overall population.
It is very important to choose a statistical analysis that is appropriate for the type of data collected.
Try to keep the commentary on the conclusions objective rather than subjective.
Make sure to label the axes of all graphs, label them correctly and try to select a style of graph that best conveys your message. Avoid the use of 3D graphs as they can often detract from the readability of a graph. Choose the graph type that is appropriate for your data, for example, do not use line graphs to summarise categorical data.
In presenting your results, limit the number of decimal places displayed to 2 or less – unless the data specifically needs to be displayed with more decimal places.
Take care with spelling and the overall alignment and formatting of the poster. Try to avoid having too much text and over-filling the poster area. Use a mixture of text, graphs and images, but keep in mind graphs and images have a greater impact than text.
Do not over-complicate the flow of the narrative.
Make sure all text, graphs and images are legible in the final poster.
Try to create an eye-catching poster but be careful in choosing the overall colour scheme, 2 – 3 different colours should suffice. Use an overall colour scheme that is not too garish and hard on the eye. Avoid backgrounds that are too busy.
Originality and creativity in the research question are key components of the competition.


Here are some links to get a general idea about posters:

John Hooper 2023 Results

For information on uploading and submitting your poster: Guide on Submitting Entries

For information about other CSO Competitions and Awards → Click here