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) Visual Cues: Position, Direction, Length, Color Coordinate System: Cartesian Scale: Time

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

  3. 20,000 years ago - Length: Menarche and Psychosocial maturation are different.

  1. 2,000 years ago- Position: The variables are in a different position compared to 20,000 years ago

  2. 200 years ago - Direction:This pair rises and the shape looks wider as compared to previous variables.

  3. Present-Present:Color indicates a difference between menarche and psychosocial maturation.

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

This graph addresses the difference between the menarche and psychosocial maturation which shows a mismatch across the years (from 20,000 years ago to present day). This is done by using color which shows the mismatch between menarche and psychosocial maturation. The position, length and direction also show the differences.

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) Color and legth appear to be the visual cues. Coordinate system is cartesian.Scale is linear.

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

Color and length visual cues used for each: i. Marlboro ii.Mild Seven iii.L&M iv. Winston v. Camel vi.Cleopatra vii.Derby viii. Pall Mall ix. Kent x. Wills Gold Flake

  1. Critique this data graphic using the taxonomy described in the lecture. The graph shows 10 brands of cigarettes and their corresponding sales which is depicted by color and length. Marlboro appears to be the top brand among those listed in the graph.

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”).

This graph is simple to understand. It shows the sale of spirits, wine, beer, in March 2020 across 13 US states. It uses color, position and length to show the differences in the sales of the different types of liquor in each of the 13 states as well as the average total of each of the liquors sold in all 13 states. It appears from the graph that in terms of total liquor sales, Delaware had the highest total number of sales for all alcohol. It is very easy to identify the which type of alcohol has higher or lower sales because of color and length as the the visual cues for each state.

knitr::opts_chunk$set(echo = TRUE, message = FALSE, warning = FALSE)
library(tidyverse)
knitr::include_graphics ("~/HU -Project Management Application/Data Viz/Alcohol Sales.png")

  1. 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”).

This graph depicts the differences in mask requirements across various countries in Europe. However, it is very difficult to understand which line belongs to which country since all of the colors appear to be the same. This could have been a pie chart showing the countries that has mask requirements versus those that don’t. This also could have been a bar graph with different colors associated with the countries.

knitr::opts_chunk$set(echo = TRUE, message = FALSE, warning = FALSE)
library(tidyverse)
knitr::include_graphics ("~/HU -Project Management Application/Data Viz/Covid G.png")

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:

It was difficult to understand this graph at first glance. The overwhelming use of the color blue everywhere makes it even more confusing to understand the differences in data being represented.For example, in the first chart, different colors could have been used to show the different percentages in the demand for data scientists in the next five years. The characteristics of data science in this image is also very confusing.

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: Although the graphs are visually appealing, it is difficult to quickly ascertain the kind of information being set out here. No.14, the total meat consumption chart is a little difficult to understand because there is not clear explanation as to what it depicts. Although, the article suggests that size of the country in the map corresponds to degree of meat consumption, there is no legend, and no code followed for the colors and it is hard to understand without a title or clear explanation within the image. I would have provided a title, and created a bar chart instead, using different colors for each of the countries. Alternatively, the map could have had colors associated to the percentage of meat consumption across the countries.