## Data Visualization: The Table

What a great visual to help you decide how to visualize your data.   By studying this “visualization” you can see that tables and graphs are primarily used to summarize data and to find relationships.

## Tables vs Graphs

### Tables:

• Verbal representation
• Read the information in rows or columns

### Graphs:

• Visual representation
• See patterns or relationships

Neither one is better than the other – they each have their own merits and purposes.  It is up to you as the researcher to decide which is more appropriate for your story.

### When would you use a Table?

• Look up individual values
• Compare pairs of related values
• Need precision
• Multiple sets of values in different measures
• Show summary and detailed information

### When would you use a Graph?

• Show relationships among and between sets of values by giving them shape
• Patterns, trends and exceptions are more easily seen rather than read
• Series of values – seen as a whole

## Different types of Tables

1. Data table
• Show rows and columns of data
• Very difficult if not impossible to see any trends or relationships by looking at raw data
2. Contingency Table – or a Crosstab(ulation) Table
• Can show the relationship between two variables
• Variables MUST be categorical!
3. Summary or Aggregate Tables
• Show descriptive statistics such as: mean, minimum, maximum, standard deviation, standard error, etc…
• Can also group these by a categorical variable

## Anatomy of a Table

Remember that a table should stand on its own!!!

Highlights of the anatomy of a table.  If you are publishing, please check with the publication you are submitting to.  The guidelines listed below have been pooled from a number of different sources and are meant to be used as a teaching tool and guide only.

TITLE:  Should be clear and concise
Also known as the HEADING – according to the Operations Manual for the Canadian Journal of Plant Science, Canadian Journal of Soil Science, and the Canadian Journal of Animal Science.

• Capitalize the heading in sentence format with no period at the end
• Do not indent the second and any subsequent lines
• No units of measure in the title

COLUMN TITLES: Visible and concise

• Capitalize only the first word
• Units of measure in parentheses on the last line of the subheading
• If several headings share the same UOM, place below the headings, centred

LINES:  to separate different parts of the table

BODY:

• headings within the body of the table need to be italicized
• centre entries under the column headings
• centre data within the columns on decimal point, dashes, etc..

FOOTNOTES: used to clarify information in the table and should always appear at the bottom of the table!

• Each footnote is on a separate line
• Asterisk – * to designate statistical significance

## Examples of Tables

Data Table

Crosstabulation Table

• Under Geography – select all provinces
• Select Apply at the bottom of the page
• This will create a Crosstab table of geography vs Quarter/year

Research results table

## Designing a table

Items to think about when you are designing a table.  A statistical package may not always provide you with the ideal table 🙂

1. if you are comparing categories, these should be presented vertically in columns rather than rows.
2. Row entries of data should not be random – order them by importance or alphabetically.
3. If you are presenting more than one level of categories, arrange the hierarchy to emphasize the categories you think are most important

Example:

Steer weight                                                   Heifer weight
1981     1991     2001    2011                          1981    1991    2001    2011

Versus

1981                                                      1991
Steer weight     Heifer weight          Steer weight    Heifer weight

## Summary

• Often used to present a lot of data
• Audience will glaze over the table and may not remember the message behind it.
• Not recommended to use a table to show patterns, trends, or interactions between values – this may be easier to see and remember by using a more visual object
• Remember who your audience is!!

## Data Visualization: The Basics

Data visualization can mean many different things to different people.  To me, it all comes down to the purpose.  WHY?  and to WHOM?

Our first data Viz meeting, held on October 17 was a quick review of why we use Data visualizations, and a review of the general principles of visualization.  We then reviewed some of the graphic design principles.  Some of these come naturally to folks, while others may be a challenge.  I want to highlight the principles here and will provide a link where you can download the powerpoint that was used during the session.

Four main purposes of Data Visualization:

1. Analysis
2. Communication
3.  Monitoring
4. Planning

Remember your audience will play a major role in helping you define how you present your data and/or your results

Five General Principles behind Data Visualization:

1. Show the data
2. Simplify – you want to keep the message simple and remove all the flowery bits of your visualizations
3. Reduce the clutter – do you REALLY need all those grids or ticks on your graph??
4. Revise your visualizations – creating a graph or a table should be viewed as part of your writing.  You don’t write something and leave it.  You write, you revise, you may write again and revise again.  Treat you visualizations in the same manner.
5. Be HONEST!  This may sound funny – but let’s face it, there are times where the visualizations we create may have an element of exaggeration added in.  Those y-axes – where do they start?  at 0 or somewhere else?  Are we exaggerated the differences between those lines?

The attached powerpoint presentation also demonstrates some of the graphic design principles that we should be aware of as we create tables and graphs.  Please review these as you work on your visualizations.

## Communities of Practice: Coming Fall 2017

“Communities of practice are groups of people who share a concern or a passion for something they do and learn how to do it better as they interact regularly.”  – wenger-trayner.com

The OAC Stats Support Service will facilitate Communities of Practice (COP) to engage the OAC research community and assist with the statistical analyses and statistical software. Our researchers use a variety of statistical approaches and statistical software packages to conduct their research, by meeting, sharing perspectives, and learning new aspects of our software and/or statistical approaches, as a community, we can create enriched learning environments for all.

Fall 2017, will see the creation and revitilization of four COPs:

• SASsy Fridays
• Crimes of Statistics
• OAC R Users Group
• OAC Data Visualization

### SASsy Fridays

SASsy Fridays started as a COP in W14 in response to the growing interest of SAS-specific topics beyond what was being taught in the workshops. If you use SAS and are interested in learning and sharing new approaches to using the software or new statistical approaches in SAS, this is the COP for you!  For past topics please review the SASsy Fridays blog.  If you have a topic you would like to present or would like more information about, please email oacstats@uoguelph.ca. SASsy Fridays sessions will take place in the Crop Science Lab Rm 121A on the following dates and times:

• Friday, October 13  from 12:30-1:20 p.m.
• Friday, October 27 from 12:30-1:20 p.m.
• Friday, November 10 from 12:30-1:20 p.m.
• Friday, November 24 from 12:30-1:20 p.m.
• Friday, December 8 from 12:30-1:20 p.m.

### Crimes of Statistics

Many of us conduct experiments and run the appropriate statistical analysis, but sometimes we can get caught up in questioning the basics of the theoretical background. Topics such as replication, sampling, power, p-values, and many more. This COP will meet to discuss these and other topics. A short presentation on the topic du jour will be followed by a discussion of situations you may have encountered. The Crimes of Statistics COP will meet in the OAC Boardroom (Johnston Hall) on the following dates and times:

• Tuesday, August 22 from 10:00-10:50 a.m.
• Tuesday, September 5 from 10:00-10:50 a.m.
• Tuesday, October 3 from 10:00-10:50 a.m.
• Thursday, November 2 from 10:00-10:50 a.m.
• Thursday, November 30 from 10:00-10:50 a.m.
• Tuesday, December 12 from 10:00-10:50 a.m.

The first meeting on August 22 will be an information gathering session. Please bring any topics you would like to see discussed to this session.

### OAC R Users Group

R is growing in popularity and is gaining international acceptance in the research community. The goal of this group will be to exchange knowledge about R-packages and R-libraries that your research field or your lab uses. A short presentation or demonstration of  practical application of an R-package or R-library will be followed by questions and exploration of other uses for the presented material. The OAC R User Group meetings will take place in Crop Science Lab Rm 121A on the following dates and times:

• Friday, October 20 from 12:30-1:20 p.m.
• Friday, November 3 from 12:30-1:20 p.m.
• Friday, November 17 from 12:30-1:20 p.m.
• Friday, December 1 from 12:30-1:20 p.m.
• Friday, December 15 from 12:30-1:20 p.m.

### Data Visualization

You have been collecting data for a project and now it’s time to do something with it! What do you do? How do you present it? Should it be a table? A graph? A chart? This COP will discuss different ways of presenting data, the pros and cons of different formats, and will encourage the community to demonstrate their favourite data visualization formats. The Data Visualization COP will meet in the OAC Boardroom (Johnston Hall) on the following dates and times:

• Tuesday, October 17 from 12:00-12:50 p.m.
• Tuesday, October 31 from 12:00-12:50 p.m.
• Tuesday, November 14 from 12:00-12:50 p.m.
• Tuesday, November 28 from 12:00-12:50 p.m.
• Tuesday, December 12 from 12:00-12:50 p.m.