This graph tries to correlate vaccines with aluminum in them to autism. Aluminum, which is a metal we use in our daily lives, does not cause autism. This graph doesn't label all of its lines, and shows no causation.
On the other hand, a good graph shows how vaccines have been aiding in the eradication of diseases such as polio and measles, as shown here.
Both graphs have consistent scales, showing accurate information. It shows where the vaccine first began, and how that affected the amount of people afflicted.
The bad graph is very disorganized and does have any labeling which can make it hard to read. The second graph is much better and clearly gives more information.
ReplyDeleteKeely, you make some good points such as that for the top graph, correlation does not equal causation. In this case, the source of the data and reliability of the website the graphs came from would be really important too. So please add some information about that.
ReplyDelete-Each graph should be labeled as Figure 1, Figure 2, etc. This is how you should refer to them in the text (Figure 1 shows...)
-Include the source of each graph either under the graph or at the bottom of the blog post
-Discuss how the data was collected for each graph, who created the graph and their reliability as experts in this topic, that kind of thing.
Keely, you did not address my feedback. Please remember to do so in a timely manner for future blog posts so you don't lose any points.
DeleteI think you have great examples of both good and bad graphs. That bad graph really is quite terrible haha, it probably just confuses parents trying to research vaccines. Nice post!
ReplyDelete