ANLY 512 Problem Set 2

Introduction to Data Visualization

Directions

In this chapter we discussed why well-designed data graphics are important and we described a taxonomy for understanding their composition.

The objective of this assignment is for you to understand what characteristics you can use to develop a great data graphic.

Each question is worth 5 points.

To submit this homework you will create the document in Rstudio, using the knitr package (button included in Rstudio) and then submit the document to your Rpubs account. Once uploaded you will submit the link to that document on Canvas. Please make sure that this link is hyper linked and that I can see the visualization and the code required to create it.

Question #1

Answer the following questions for this graphic Relationship between ages and psychosocial maturity

1. Identify the visual cues, coordinate system, and scale(s).

• The graphic uses Cartesian coordinate system, the x axis is for time periods, the y axis is for age. Also, Time scale is used. As for the visual cues, we can point out color, length, position, direction

2. How many variables are depicted in the graph? Explicitly link each variable to a visual cue that you listed above.

• There are 4 variables. Menarche and Psychosocial maturation are dependent variables. They can be distinguished by color (Menarche is green and Psychosocial maturation is pink). Age and Time period are independent variables and are used for scale. Length of each candle depends on the Age values for dependent variables. Position of the candles depends on the Time period. Direction is dependent on the combination of Age and Time period.

3. Critique this data graphic using the taxonomy described in the lecture.

• The graphic allows us to compare Menarche and Psychosocial maturation based on the position and length of candles. Different colors let us distinguish between the two dependent variables. We can see the change in directions and age ranges from one Time period to another.

Question #2

Answer the following questions for this graphic World’s top 10 best selling cigarette brands 2004-2007

1. Identify the visual cues, coordinate system, and scale(s)

• Visual cues: color, length. Coordinate system is Cartesian. X axis has linear scale, Y axis has a categorical one.

2. How many variables are depicted in the graph? Explicitly link each variable to a visual cue that you listed above.

• We can see 2 variables: Cigarette brand and Sales. Color is used to distinguish between different cigarette brands. Length of a candle helps to show sales values for each brand.

3. Critique this data graphic using the taxonomy described in the lecture.

• The graphic provides an insight on the World’s top 10 best selling cigarette brands between years 2004 and 2007. Different colors make it easier to distinguish between brands while different candle lengths allow us to easily compare sales volumes for these brands.

Question #3

Find two data graphics published in a newspaper on on the internet in the last two years.

1. Identify a graphical display that you find compelling. What aspects of the display work well, and how do these relate to the principles that we have just gone over in lecture. Include a screenshot of the display along with your solution (Hint:use the following in a code chunk: knitr::include_graphics(“your_graphic”).

knitr::include_graphics("Student loans.png")

- The above graphic is compelling to me since it is the bar plot that is easy to interpret. I can see how many borrowers belong to each amount owed bracket. It is pretty simple as there are only two variables.

2. Identify a graphical display that you find less compelling. What aspects of the display don’t work well? Are there ways that the display might be improved? Include a screenshot of the display along with your solution (Hint:use the following in a code chunk: knitr::include_graphics(“your_graphic”).

knitr::include_graphics("Tax Filings.png")

- This graphic is bit harder to read as it has a few shades of green depending on the returns count. It needs a little more time to interpret compared to the one before. I don’t really have a better solution though. I think it is just the specific of information represented here.

Question #4

Briefly (one paragraph) critique the designer’s choices. Would you have made different choices? Why or why not? Note: Link contains a collection of many data graphics, and I don’t expect (or want) you to write a full report on each individual graphic. But each collection shares some common stylistic elements. You should comment on a few things that you notice about the design of the collection.

What is a Data Scientist

Answer: I think the choice of colors is fine. Some graphics feel a bit overwhelming with the amount of information on them, for example the one comparing proportions of BI professionals vs Data scientists in learning backgrounds.

Question #5

Briefly (one paragraph) critique the designer’s choices. Would you have made different choices? Why or why not? Note: Link contains a collection of many data graphics, and I don’t expect (or want) you to write a full report on each individual graphic. But each collection shares some common stylistic elements. You should comment on a few things that you notice about the design of the collection.

Charts that explain food in America

Answer: Graphics 2 and 4 are simple and easy to read. I would do these in a similar way. Graphic 3 is also pretty easy to interpret and see the trends based on colors depending on geography. At the same time, if we take a look at graphic 5, it seems harder to read as there is a multiple choice of colors, shades and transparency thanks to the gradient. Graphic 38 has similar problem, especially when there is no obvious leading name (soda, pop or coke). However, figures 28 and 29 are even harder to work with. For graphic 28, according to its description, each point has the colors of the three most popular restaurants at that location. Personally, for me it is extremely hard to name three most popular restaurants at any point on the map. On graphic 29, it isn’t easy to determine state borders or major cities. It is creative but its interpretation would be easier if the base map was shown as on the figure 3 and density be visualized by color shade, not the “waffle” candles’ height.