Assignment 5

This map is made up of the data set provided in class, of homicides in Chicago.

Assignment 4

Figure 1 is a Descriptive model. It's a summary of the given data, most often used as a table or graph. The data presented is organized and presented in a way that displays the most obvious features about it. From the charts we could reasonably deduce the mean, median, and mode of the data and see if there is any skewness. 

Figure 2 is a Predictive model. The chart is predicting what the scores of the students and instructor will most likely be based off the given data. It cannot predict the future-however it can determine what might happen that includes risk assessments in its analysis. Predictive statistics typically help business owners understand their customers better, identity new opportunities for growth, or spot a potential problem. For this figure, it predicts the scores will lower based off previous data. 

Figure 3 is a Inferential model. It draws conclusions based off a sample of a bigger data set. This particular figure wants to know if Rick Perry has a chance of winning in the upcoming primary election. Asking every registered Republican in the nation would be impossible, so the chart draws from a smaller sample-a poll. Measuring a sample of a bigger population draws conclusions about the population as a whole. 

Assignment 3

Robin Camarote's "4 Great Resources for Presenting Your Data Creatively" list resources that can help inspire anyone who needs to create a data visualization. Each source contains sample charts/graphs/other visualizations that help fully convey how differently information can be displayed. The article, like the lecture, explains that people need visualization in order to fully understand the full scope of big data. While regular bar graphs are appropriate for some projects, creativity for visualizations can also be rewarding.

Another article on Forbes, "Big Data Needs More 'Creative Types'", explains that the data science field should be populated with creative, arty people. These people, whom the article refers to as "data artists" are able to combine knowledge about statistics and problem solving skills to successfully portray a story out of large amounts of data. In the lecture it was explained that some data visualizations are able to point out certain trends or inconsistencies more than others. Data artists are able to discern patterns from information in unconventional ways, that most people simply are unable to do.

Denise Lu's "7 Data Viz Sites to Inspire Your Creative Eye" features a list of sites that display interesting, out of the box, visual displays of data. Some sites put more of an emphasis on the asethetics they offer while others are optimal for different types of data. For example, "Chart Porn" is frequently used for political and financial graphics. The lecture gave examples of several measurements of data (gender, Twitter users, etc) out of the many possibilities. Knowing about as many visualizations as possible makes it easier to think up new ways to display a given data set.


Referenced articles:

http://www.inc.com/robin-camarote/look-smart-with-inspiration-from-these-top-4-data-visualization-sites.html

http://www.forbes.com/sites/teradata/2015/01/30/big-data-needs-more-creative-types/

http://mashable.com/2013/10/01/data-viz-sites/#gkbjZh.qDuk_

Assignment 2

The first program I tried to open the data with was Google Spreadsheets, since I had never used it before and was curious about trying it out. It kept crashing so I moved on to using Excel. From what I can gather, the document appears to be a list of programs used by various companies. The spreadsheet includes the acronym and id for the program and lists the company that uses it, along with their mailing address. It also includes two columns "start date" and "end date" that I'm assuming are for how long the company uses the program for. However, I'm not sure what a few of the columns are supposed to represent, including "duns number" and "ein."

Assignment 1

Hi! I'm Bridget White. I'm really looking forward to learning how to use different kinds of spreadsheets. I was just mentioning to a friend a few months earlier that I'd love to learn how to use at least Excel so I'm excited that this class is using even more programs. The visualization that caught my eye the most was Kenneth Buker's example. It looks really intricate and unique-I almost never see data presented in that kind of way and I spent a few minutes looking at everything on it. It excites me to know that I'll be able to make something similar to that by the end of the class.