Scientific Data or data alone can be represented in many different styles. Through representations using bar graphs, histograms, line graphs, and dot plots, many individuals can produce, study, and share these specific findings and data. Data itself though can be represented well or poorly. Through individuals own perspectives and interpretations, data and information can even be correct and poorly portrayed. In scientific findings, individuals creativity can either make or break data. With breaking down poorly created graphs, we as individuals need to be aware of how we read information and find exactly what we are looking for within a graph. Below are some examples of how poor data can be represented.
Unlabeled and Discontinued Axes
Graph A
http://uk.businessinsider.com/how-many-concussions-in-the-nfl-2016-1
Using this bar graph, we can see this unlabeled axes can be rather confusing due to its vague to nothing representation of not knowing exactly what it is. Graphs A, like these can confuse readers into not allowing them into not knowing what the X and Y axes represent and what the individuals who made the graphs are wanting to portray to readers.
Graph B
https://www.omicsonline.org/open-access/rheological-model-of-force-transmission-through-2376-0281-1000132.php?aid=34315
Using Graph B to porttray this discontinued axes graph does not allow for us to see how and where the data points should end and begin. This is hard for individuals reading the data to fully comprehend and interpret the data with starting and ending points and said information.
Better example of a Labeled and Continued graph
Graph C
https://www.emaze.com/@AQCLTWRI/Concussions
Graph C better identifies a proper labeling axes and continued graph with proper points. This is important due to portraying and interpreting information for viewers. Graph C projects a better interpretation of how the top five sports played by kids provide concussions.
In high school, I was taught how to properly find, retrieve, and weave out of false information. My AP Psychology teacher my sophomore year of high school did a whole unit on statistics and collecting and retrieving valid and refutable data. This allowed me to develop a tool to find proper information that I can use for my own benefit. Through my own experiences with graphs and data, I have not been lead to false information. Improper scaling, discontinued and unlabeled graphs can cause major confusion within not only presentations of information in the mass media, but as well as the interpretation in education and health related fields.
This is a great and well thought out blog post. I feel significantly more informed about this topic now.
ReplyDeleteGreat blog post. I like how you had a good introduction before showing the graphs. Also, good job on finding two graphs that are confusing and showing how the proper one should be formatted.
ReplyDeleteI like how you broke down the good and bad examples of graphs because it can really help people understand that graphs can give misleading information. Great blog post! Very well thought out.
ReplyDeleteOkay Nik, this is a great start, but you need to go back to the guidelines for this post on the ASU Learn page and reread them. You need to find examples of good and bad graphs related to your final project topic and discuss them. Also, keep these pointers in mind:
ReplyDelete-When you include images/ graphs, it's better to label them Figure 1, Figure 2, etc. Then you refer them to them as such when discussing them in the body of the text. This makes it easier to follow what image you are referring to and also makes the writing better in general.
-If you include an image, make sure it's the right resolution for the post, not blurry or pixelated. This is difficult for some, but play around with them.