In the lecture on continuous joint probabilty the example is given of call center wait times vs customer rating. The data is initially depicted as a scatter plot, and then a heatmap - the heatmap being generated by binning the data I am guessing. So far so good.

From there though a 3D graph of the joint probability density is shown which appears to be continuous for joint probability (i.e. is a combined PDF for both distributions) however there is no explanation for how this is generated which is the whole point of the lecture - how is a continuous PDF for two variables actually produced, how are the probalities for the graph generated? It does not explain in the lecture and in the following lecture the graph is then used again for extracting the marginal distribution but it is not explained what function is being used to generate the PDF in the first place.

Is it possible a slide or video is missing as it seems quite crucial for this section?

I’m sorry for asking another question but I am really trying to understand this topic.