BUS612: Data-Driven Communications

4a. Compare visualization tools and apply visualization techniques

• What goals can be accomplished by using visualizations?
• What are the tools and capabilities of a robust visualization tool such as PowerPoint?

Visualization tools are an important nonverbal aspect of your presentation that is completely in your control. The purpose of each visualization should be clear and almost speak for itself. Visualizations can significantly develop a presentation and should have a specific purpose the audience can easily recognize. They can also provide emphasis, effectively highlighting keywords, ideas, or relationships for the audience. They can also support a position by utilizing recognized authorities or multiple sources in graphic form. Clarity should be a key prerequisite for using visualizations. Several ways to improve clarity include limiting text on slides, using the right font size, using key images, or presenting the same data in two distinct formats, such as a line graph followed by two pie graphs. The central goal is to ensure the visualization is clear.

PowerPoint can be used to present a variety of visualizations. Its ability to integrate with numerous other applications and formats makes it an essential tool to master. Approach your visualizations with an iterative mindset, recognizing how you initially envisioned it may look completely different from the final product.

To review, see Visual Aids.

 

4b. Describe data findings through visual charts, graphs, and dashboards

• How would you compare the different manners to present data numerically and graphically?
• What are the differences between a data set's mean, median, and mode?

Data has been collected from surveys or experiments; it needs to be summarized and presented in a way that will be meaningful to the reader. It can be presented in numerical summaries or graphical presentations.

The center or midpoint of a data set helps describe its location. The mean and median are the two most widely used measures of the data 'center'. The mean, also called the average, is the total values divided by the number of values. The median is the middle number that splits the ordered data set into two equal parts. It is often used when the data has extreme values or outliers since precise numerical values do not affect it. Another measure of the center is the mode, which is the most frequent value. A data set can have more than one mode as long as the values have the same frequency.

 

Example of a Mean

Here is an example that uses the number of cans of paint bought at a home goods store, sorted by color. The total number of cans of paint bought at a home goods store for each color is recorded as follows:

Red: 12
Blue: 9
Green: 6
Black: 14
White: 18
Silver: 21
Gray: 20
Other Colors: 15

Adding these values, we obtain a total of 115 cans of paint. Dividing by the number of color categories (8), we find that the mean number of cans of paint bought is 115/8 = 14.375. Rounding this to one decimal place, the mean is 14.4.

 

Example of a Median

To calculate the median, we list the number of cans of paint bought in each color in ascending or descending order:

6 9 12 14 15 18 20 21

Since there is an even number of color categories (8), the median is the average of the two middle values, which are 14 and 15 in this case. Adding these two values and dividing by 2, we find that the median number of cans of paint bought by color is (14 + 15)/2 = 14.5.

In this particular example, the mean and median values are fairly close to each other, indicating a relatively balanced distribution of cans of paint bought across color categories.

A frequency table lists each item and the number of times the item appears. The level of measurement is how a data set is measured and can vary with the type of data being analyzed.

To review, see Describing Data.

4c. Organize data visualizations to convey messages and main points

• What are the best practices for creating meaningful and effective data visualizations?
• What thought process is involved in summarizing survey data into meaningful visualizations?

The human visual perception system is very powerful. When utilized properly, visualizations allow for a greater understanding of the data. Analysts need to understand how to best communicate visual information for greater understanding. It is important to keep it simple, be communicative and powerful in your data storytelling.

With better software, faster processors, and cheaper memory, it has become easier to create and iterate visualizations. With this power comes responsibility, as it is very important to create good visualizations that clearly articulate the point the analyst is trying to make. Visualizations can be effective or ineffective, which can generate very strong feelings either way.

When summarizing data for a presentation, it is important to take an iterative approach to the graphics, colors, and audience. Remove as much extraneous information as possible to enable the audience to quickly and easily reach the best conclusion from the information presented.

To review, see Best Visualization Practices.

 

Unit 4 Vocabulary

This vocabulary list includes the terms you will need to know to successfully complete the final exam.

• center
• frequency
• frequency table
• mean
• median
• mode
• PowerPoint
• visualization tools