Quick links to content on this page
- Templates: Templates so you don’t reinvent the wheel.
- Content: Sections within the poster
- Aestetics: Font, tables, graphics, colors, logos,
- Printing: Guidance, location and prices
- Evaluation: grading rubric
- Examples: Selected examples
- Build your poster using a powerpoint template, not Google Slides.
- Trifold tabletop templates are seldom used.
- Choose either a three, or four column layout.
- Choose the correct scaling.
- Biology Student Research Symposium [website] - Additional templates and guidelines included.
The following sections of information must be included in each poster. The choice of design, boxes, columns is up to you. The direction of the story should go top to bottom, then left to right. Read in columns, not rows.
- Author list should have the form Last, MI., Last, MI.
- Affiliations can be listed many ways. Your best bet is to look at other posters presented at the same event form a prior year. For a class project, simply state your year, class and section number.
- Probably the only part that will be in paragraph form.
- This is your lead-in, the part that sets the stage for your analysis.
- Limited background and lit review go here also.
- Your research hypothesis should be clearly stated here.
- Methods (Data collection and analysis)
- Where did your data come from?
- Clearly state the variables that you are using, and any major recoding done (truncation, subsetting).
- Describe the statistical analysis methods you used.
- Include a sentence about what variables were tested as moderators and/or confounders.
- Sample characteristics
- This is where Table 1 goes, a concise univariate description of your sample.
- Analysis sample size, N(%) for each categorical variable, mean(sd) (or mean/median) for each continuous measurement.
- No more than 2 graphs or tables for bivariate comparisons
- One multivariate table or plot. The
coefplot()function in the
armpackage is an excellent way of displaying the results of a MV model. Save the results of a model as an object
my.model <- lm(your model here)then call
coefplot(my.model)on that object. (Want to roll your own? Check out this SO post)
- At least one coefficient, the primary explanatory variable, must be interpreted in context of the problem.
- You are just stating results here, not justifying, explaining or connecting any meanings.
- Summarize results in English sentences
- Draw and describe the big picture conclusions. Connect the breadcrumbs discussed in the results section.
- Make sure every statement here is backed up with evidence shown in the results.
- Why should someone care about this research?
- Connect to current research. Possibly more citations here.
- Font size can be reduced to 8 or 6 minimum.
- Acknowledgements & Contact info
- Any help you received from a person not listed as an author should be acknowledged.
- For class projects that are not presented elsewhere, I do not need to be acknowledged.
- The first author should include their contact email.
- If you have no acknowledgements, you can stick your email address in the bottom right corner as a footer.
- Readable from 10 feet
- This tends to be at least 18-20 pt font. If using a template provided
- Bullets vs. Paragraphs: Pretty field specific.
- Often the introduction or abstract is the same paragraph used when submitting the abstract for consideration.
- Walls of text tend to not be read.
- White space: Also somewhat field specific. You want the poster to be readable and eye catching.
- Build them in Excel, or PowerPoint tables directly
- Use borders for the top, and bottom of the table
- Use vertical borders sparingly. Probably only for the far left corner.
- Excel has some good auto-formats you can use.
- Do not copy/paste from anything, it won’t scale up well.
- Finalize the plot, then save it to your computer using the code below
- Specify height and width in pixels. You know your monitor’s aspect ratio? 800x600? 1280x800? Those are in pixels.
- Start with 400-600 and see what it looks like.
png("C:/YOUR PATH HERE/filename.png", width=400, height=350) # open the graphics device. plot(iris$Species) # your plot goes here dev.off() # this closes the graphics device
- Always best to save the file larger rather than smaller, then manually shrink down in PPT
- You can increase the base size of text in your graphic (so it looks reasonable once you export) by adding a
base_size=argument to your
theme(). I would suggest starting at 18. I.e.:
- Want to see what it’ll look like when scaled up? Follow the instructions on [How will my poster look when it’s printed?].
Your poster is a professional publication. It should reflect your campus properly and following guidelines (where they are listed). Every campus has official logos, colors and instructions on how to correctly use these. Below I have linked the ones I could find for Chico State.
- [University Naming]
- [Color Palette]
- [Logo and Seal]
- This page is not fully developed yet, only the seal is available for download on this page.
- [Other unofficial logos]. Note that the use of the wildcat is not allowed unless you are discussing Athletics. Stick to using the Seal, or flame logo.
- Colors are good - but stick to a theme/pallet.
- Make the colors meaningful. There’s nothing informative about a rainbow.
- R Cookbook guide for colors in ggplot2: http://www.cookbook-r.com/Graphs/Colors_(ggplot2)/
- Don’t wait until the morning of to print - this is ESPECIALLY true in Spring when there are multiple poster symposiums being conducted.
- You can print in B&W, and any color graphics can be printed on 8x11 and taped onto the poster.
- Don’t spend a fortune!
Prices are student reported as of Fall 2016.
- Staples ($65)
- Metagraphcs $50 36x48 –still pricey
- Ellis Art (downtown and on Esplanade) $30
- Kinko’s downtown, B&W $10
I use the following criteria to score posters. You can also [download] the rubric as a Word doc for printing.
- Display attracts viewer’s attention.
- Words are easy to read from an appropriate distance (3-5 feet).
- Poster is well organized and easy to follow.
- Graphics and other visuals enhance presentation.
- The poster is neat and appealing to look at.
- Content is clear and easy to understand.
- Purpose of model (question being addressed) is stated clearly.
- I understand why someone might be interested in the model results.
- There is enough detail about methods (e.g., creating new variables) for me to understand the model and results.
- The sample characteristics are fully described.
- The approach taken is appropriate for the problem and technically sound.
- Conclusions are stated clearly.
- Conclusions are supported by model results.
- Limitations of the study are clear.
- Presenter’s response to questions demonstrated knowledge of subject matter and project
- The presenters conducted themselves professional during the presentation.
- It was clear that all team members understood what was being presented and had an equal contribution to the data analysis. One member did not dominate the presentation and questions.
A selection of sample posters, class projects have comments regarding what made them stand out, and what could be improved.
- Patterns of Sexual Experience Among an Urban Sample of Latino and African-American 9th Grade Students Jeffries, RA., De Rosa, CJ., Moulton, B., Chung, EQ.
- Sexual Identity and Associated Factors Among and Ethnically Diverse Sample of 9th Grade Public School Students Viola, R., Jeffries, RA., Moulton, B., De Rosa, CJ.
- Pre-sexual behaviors as predictors of sexual risk in adolescents: Examining alternate outcomes in sexual health education programs Moulton, BD., Donatello, RA., Rohrbach, L., Afifi, A., Meyer, KI., Leon, P., Lau, C.
- Implementing a Flipped Classroom and Active Learning Techniques in General Chemistry to Augment Student Success at a Mid-Sized Rural University Smith, M., Aguilar, R., Cherrette, V., Rose, A., Crane, J., Park, C., Bladorn, E., Mills, H., Sherry, S., Chatha, C., Park, H., Dailey, H., Donatello, RA., Wasinger, E.
- Moving Away From BMI: Lifestyle and Biological Factors Impacting Health Brooke,C., Corona,J.,Kessner S.,Lona,I.
- Great additions to the univariate plots of BMI and Cholesterol. Tables are clean, could use bigger font. Sample characteristics only a list of variables. Not enough info on analysis methods, or explanation of Figures 2 and 4.
- Do Field Dimensions Affect Baseball outcomes? Stolenberg R., Williams K., Harris A.
- Excellent use of whitespace, colored tables that match the theme. Plots are difficult to read, font size is great, but paragraphs are harder to read than bullet points.
- Effects of Childhood Social Support on Trauma Hostler, M., Thornton A., Wong R.
- Clearly laid out variables of interest and RQ’s. Good use of pie charts. The 3D scatterplot is not helpful. Model results presented in a nice table, but not explained.
- Using 2010 U.S. Census Demographics to Determine a Predictor for Beer and Wine Consumption Ellis, C., Esposito, C., LaGrange, A.
- Great use of maps, model comparison table in the bottom middle. Bullet points clear and easy to read. Univariate summary statistics very clearly laid out.
- The Associations Between Familial Relationships, Daily Activities and Delinquency in Adolescents Guetta, R.
- Very clearly laid out RQ’s and introduction. Discussion connects to current literature.
- Trends in Avian Influenza at Howard Slough Aguilar, R., Antonio, A., Balkow, N., Dehoney, T., Ling, D., Saenz, J., Urlie, L., Cline, T.
- Good balance between tables and graphics, cute duck. Results clearly explained using N(%) in text.
- The Effects of Voter Demographics on the 2016 Primary Elections Jordan, A., Arriaza, L., Ejaz, N., Loeblich, A., Wain, C.
- Watermarks on bottom corners make words difficult to read. Table under results not made in Excel. Not easy to follow direction of story