Also, side-by-side histograms aren't the only way to display two parameters in a single histogram. What about stacked histograms? They scale up to an arbitrary number of parameters and everybody who can read a histogram can read a stacked histogram. Scatter plots seem like thermonuclear overkill for a problem which most movie sites seem to consider to be "solved".
Read the text of the article describing each movie. The correlations are absolutely meaningless. He doesn't hit on them at all. In fact, with comments like "almost nobody" he's specifically looking at averages. Then coming to a conclusion effectively based on the average of Score 1 and the average of Score 2 to determine what type of movie it is.
So on this Quality/Rewatchability grading system:
Starship Troopers: 3:4 The Fifth Element: 4:4 Blade Runner: 4.5:3.8
Drop that in place of the graphs and the conclusions would sound as seemingly valid.
It would be nice if the article actually compared different visualizations of the same data, rather than showing histograms of 2 separate data sets and scatter plots of a 3rd data set.
A scatterplot conveys objectively more information.
Actually it is fundamentally different as the histograms show aggregate data and scatterplots show individual data points.
As far as reading the distribution, two separate histograms are definitely more readable and understandable in order to understand the distribution. Adding the complexity of a scatter plot because it also shows a correlation that people are not actually interested in makes things less understandable.
Yes it would, and the article shows why and how. Scatter plots are easy to read (for comp./math. educated people). Two histograms side by side are easy to read (and find correlations) for nobody.