Please answer the following two questions that pertain to Lecture 13 and Lecture 14.

  1. Do dimensionality reduction techniques, in the context of visualization, provide item aggregation or attribute aggregation? Consider visualizing dimensionally-reduced data using a two-dimensional scatterplot. Describe one type of task where such a visualization could be useful. Describe a situation where such a visualization could mislead.

  2. State three possible axis orientations that can be used for arranging tabular data. For each orientation type, state one possible visualization that uses it to show a table that has more than two attributes. Given a high-dimensional dataset (i.e., more than 20 dimensions), which orientation would you prefer and why? You are encouraged to justify your choice using whatever interactions, visual encodings, and any other techniques from class.

Grading

Submit your quiz in a folder called quizzes in your git repo. Within this folder create a file Q05.txt that has your answers.

For each question, I’m expecting an answer of 150 words or less. Aim to answer each question in a single paragraph.

I plan to grade your answer on a scale of 0-5, where 5 indicates that you completely answered all portions of the question. Thus, you will receive a score of 0-10 for this quiz. This score will be scaled to the total value of this quiz for your final grade (1%).