diff --git a/02_activities/assignments/assignment_2.md b/02_activities/assignments/assignment_2.md index 7bb5b2df7..8d09486a6 100644 --- a/02_activities/assignments/assignment_2.md +++ b/02_activities/assignments/assignment_2.md @@ -10,25 +10,13 @@ - For each visualization (good and bad): - Explain (with reference to material covered up to date, along with readings and other scholarly sources, as needed) why you classified that visualization the way you did. ``` - Your answer... - - - - - - +An example of a "bad" data visualization is Figure 1B of DellaVigna and Gentzkow (2019, QJE). This figure displays the log prices of 5 products in 5 different product categories across stores over time. The quality of the data visualization is as follows. Firstly, the prices for all of the products are displayed using a monotone colour scheme which is not very pleasing to look at (although, the authors may have done this intentionally to emphasize the prevalence of uniform pricing, which is the goal of their paper). Secondly, since the paper was published in QJE (a top 5 journal in Economics), we can be reasonably confident that it accurately represents the data, as reviewers and technicians would have looked it over in detail and attempted to replicate its results. Thirdly, the message of the data visualization is understandable from context but arguably not from the visualization itself. Lastly, the names of the 5 products used in the data visualization were not provided anywhere, so it is difficult to say how representative these products are of the overall trends in uniform pricing. +An example of a "good" data visualization is Figure 2 of Strulov-Shlain (2023, ReStud). This figure displays the estimated log quantity demanded for 37 products. This quality of the data visualization is as follows. Firstly, the demand curve across dollar ranges are colour-coded, which makes the figure pleasing to look at. Secondly, since the paper was published in ReStud (a top 5 journal in Economics), we can be reasonably confident that it accurately represents the data, as reviewers and technicians would have looked it over in detail and attempted to replicate its results. Thirdly, the message of the data visualization is immediately understandable from the figure itself, as one can see the drops in demand at the dollar digits (the visualization is attempting to show that consumer demand exhibits left-digit bias). Lastly, while the names of the products used in the data visualization where not provided anywhere, the range of their elasticity estimates were, which allows the reader to ascertain some information of their representativeness. ``` - How could this data visualization have been improved? ``` - Your answer... - - - - - - - +The "bad" visualization could have been improved by using a less monotone colour scheme and providing more details about the products used. The "good" visualization is already very good, but perhaps it could have been improved by providing even more information about the products used, such as where they are sold. Essentially, I believe that for the purposes of these two papers which are both trying to illustrate product and demand characteristics of retail products, it is important for the reader to understand how representative the illustrations are. ``` - Word count should not exceed (as a maximum) 500 words for each visualization (i.e. 300 words for your good example and 500 for your bad example)