Statistical Critique 1

1 Assignment Details

In your first statistical critique will focus on critiquing a key aspect of any statistical argument—data visualization. You have explored data visualizations over the last two weeks, thinking about what makes a plot more or less clear. You will use your knowledge of data visualizations to provide a critique for two different styles of visualizations, (1) a “pop” visualization, and (2) a “scientific” visualization.

1.1 Including your Visualizations

You are expected to include the two visualizations you decide to critique. These visualizations must be included in the paragraph surrounding your critique. Please do not include the images at the end of your document.

Getting your visualizations

For the New York Times visualization, you can left click on the image and save it to your computer.

Figure 1: Options when left clicking on NYT visualization – select “Save Image As…” to save it to your computer

For the visualization from your research article, you may need to take screenshot of the page and crop it to only include the image.

Figure 2: Cropped image from scientific article
No Visualization in Article

If the article you selected does not have a visualization, you are permitted to substitute a table for a visualization. Similar to the instructions above, you are required to take a screenshot of the page and crop it to only include the table.

1.2 Submission

You are allowed to use any text editing software to make your critique (e.g., Word, Pages, Google Docs), but your submission must be a PDF. If you are unsure how to save your file as a PDF, I recommend using Google!

2 Part One: Pop Visualizations

It is common for blogs and online news to use visualizations to convey information to their readers. In this segment you will select a “pop” visualization and provide a critique of what the visualization does well and where it could be improved.

2.1 Getting Started

  1. Go to the What’s Going on in This Graph website

  2. Scroll through the weekly graphs and click on a plot that you are interested in

  3. Save the image to your computer (as instructed above)

  4. Insert the image in your document (before your written critique)

2.2 Visualization Critique

Your critique of the visualization you selected needs to address the following questions:

  1. What aesthetics are being used in the plot?
Aesthetics are Mapped to Variables

Remember, aesthetics map variables to aspects of the plot. If your plot uses color, but the color is not associated with a variable, then color is not an aesthetic in the plot.

  1. Name at least two things the visualization does well — What makes the visualization clear to the reader?

  2. Name at least two ways the visualization could be improved — What would the reader struggle to understand?

3 Part Two: Scientific Visualizations

It is becoming increasingly common for scientific articles to be required to provide visualizations of the data alongside a statistical analysis. In this segment, you will use the scientific article you selected in Week 1 (your submission to the Week 1: Statistics in Your Field assignment) and provide a critique of what the visualization does well and where it could be improved.

3.1 Getting Started

  1. Access the research article you selected in Week 1. If you cannot find it on your computer, go to the Week 1: Statitics in Your Field assignment

  2. Locate the visualization (or table)

  3. Take a screenshot of the visualization / table

  4. Crop the image to only include the visualization / table you are critiquing

  5. Save the image to your computer (as instructed above)

  6. Insert the image in your document (before your written critique)

3.2 Visualization / Table Critique

Your critique of the visualization you selected needs to address the following questions:

  1. What aesthetics are being used in the visualization / table?

  2. Name at least two things the visualization / table does well — What makes the visualization clear to the reader?

  3. Name at least two ways the visualization / table could be improved — What would the reader struggle to understand?

If you are referencing a table

Similar to a visualization, the aesthetics of a table are variables being mapped to aspects of the table. Below is a table from Coyne et al. (2020). I like to think of the rows and columns of a table as similar to the x- and y-axis of a visualization.

An image of a table from a scientific journal.

  • I start by noticing that the “study variables” are mapped to the rows (e.g., Social Network, Depressive Sym., Anxiety).
  • Then, I notice that the columns are associated with different values of Age.
  • Finally, I notice tha there are actually two rows per study variable, one associated with the mean and one associated with the standard deviation.

If I were to sketch out how this table would translate into a visualization, I would imagine the x-axis would be Age, the y-axis would be the value of the variable, there would be three facets (one per study variable), and there would be two types of points (one for the mean, one for the standard deviation). Here is a rough sketch of my mental image:

A drawing of how I would convert the table into a visualization. There are two plots, one with a title 'Social Network' and one with a title 'Anxiety', representing two of the variables the study researched. Each plot has an x-axis with different values of age (ranging from 13 to 20), and a y-axis ranging from 0 to 5. For each age, there are two points plotted. One point is plotted as a red triangle, representing the mean value for a specific age. A second point is plotted as a green circle, representing the standard devation for a specific age.

In this plot, there are four aesthetics:

  1. the age (included on the x-axis)
  2. the study variable (included as facets)
  3. the statistic measured (included as a color)
  4. the value of the statistic (included on the y-axis)

References

Coyne, Sarah M., Adam A. Rogers, Jessica D. Zurcher, Laura Stockdale, and McCall Booth. 2020. “Does Time Spent Using Social Media Impact Mental Health?: An Eight Year Longitudinal Study.” Computers in Human Behavior 104 (March): 106160. https://doi.org/10.1016/j.chb.2019.106160.