Alex_Mao.txt

2/16/15 - Oftentimes, it can be hard to keep track of how many friends that you have. I hear there is a number (around 100?) that people have proven to be the maximum number of connections that you can keep in your mind at once. Stemming off of this idea, I wonder how much time you have to spend with someone to guarantee that you are one of the 100. Essentially, how much time do you need to spend with someone to guarantee that they don’t forget you? How could you statistically prove that number? Perhaps you could then better decide how you want to spend your time with your friends.

2/21/15 - Today at lunch I had an interesting conversation with some people about trains and how they are priced with respect to other modes of transportation. One hypothesis I had was it might have to do with the fact that it was catered more towards business people and they aren’t spending their own money. As a result, this pushes up the price for average consumers. I wonder if there is a way to statistically model this and to show the effect this pricing may have on other modes of transportation. How would we take into account differences in the actual modes of transportation themselves, especially things such as comfort? Would this have to be done through survey or is there a more rigorous way of doing it?

2/22/15 - Today I ran across a very interesting graph online (http://www.npr.org/blogs/money/2015/02/11/384988128/the-fall-and-rise-of-u-s-inequality-in-2-graphs) that I thought was reflective of some things we learned in class. The graph plots the average income of the bottom 90% against the average income of the top 1% and sees how this relationship changes over time. It is captured in two different ways and both ways have pros and cons. I thought the animated graph was actually very informative and was able to draw attention to specific things. It explained the graph in the way the author intended and it clearly illustrated the trends that the reader was meant to see. It was nice to see the trade-offs between the two different graphs and to think about what each of them was communicating
2/23/15 - With the recent winter storms, there was a particular graphic that caught my attention (https://twitter.com/EricHolthaus/status/567350490912931840). It is an animated heat map of North America that displays each region with respect to its expected temperature. It is a graphic that I want to be able to know how to make by the end of this class. It encompasses different areas that we have already touched on in class (using maps, 2 color scale, etc). I thought it was a good way of displaying the data and really letting it speak to the audience. It parallels something that audience members would be familiar with (weather forecast diagrams), so I think it does a really good job of conveying the data. I hope I will be able to make one.

3/1/15 - One thing that I thought would be interesting to test and see has happened in current events is how the weather has affected the sale of Girl Scout Cookies. I have not seen many of them and I am wondering what the implications may mean for the group. How much has weather affected these sales? Have sales been centered in certain areas? It may be good to do some research on this so that girl scouts can prepare next time there is weather like this. It would also be nice for us to know where to find girl scout cookies next time something like this happens.

3/315 - I stumbled across a statistical display that I thought would be a great example in our class (http://ncase.me/polygons/). It uses animation to illustrate how small biases in individuals can add up in a collective. The specific example in this case was about segregation and how a small seemingly harmless thought can lead to something much bigger. It was really nice because it was interactive and restrictive. It allowed users to interact with the model, but not before the author gave examples of how it worked (fixed examples). It reminded me about how Ms. Rudin from MIT mentioned that she doesn’t allow users to play with her dynamic graphs. It was interesting to see in practice. I also liked how it gave the user the freedom to do what he or she wanted to at the end. I thought it did a good job of getting the message across in a easy, fun way.

3/11/15 - Looking at the digital attack map example in class today was really cool. I thought about how real-time updates always make a visualization so much more captivating. However, it is a challenge to achieve this with many forms of data. It seems only plausible with data that relates to something online. However, this is information that may be already readily available to people due to it being online. As a result, how can we incorporate a “real-time” updating aspect to data that is connected to something offline? If it is not possible, is there a parallel?

3/16/15 - All-You-Can-Eat places always fascinate me. When at these places, people always want to get their monies worth. They eat a lot and they oftentimes pick the more expensive options. I started to wonder, do restaurants actually make more or less money through these all-you-can-eat establishments? What would you compare these establishments to to see? A regular restaurant? It would also be interesting to see how many more (or less) calories people ingest when going to one of these places. This could provide some useful information on dietary health.

3/21/15 - After coming back and talking with a lot of my friends about their spring break, I thought about how long the average vacation was for Americans. It would be interesting to break this down by age groups and by method of transportation (driving, flying, train, etc). This would probably help travel agencies in putting together packages for people. It may also be good to see how it breaks down in terms of legs of trips (a few days in one place before moving to another place). There could easily be some trends that we would see. For younger people, peak times would be around breaks and would probably be for an extended amount of time. For young working adults, the trips are probably scattered evenly throughout the year and are probably around a week or two long. Older people may have kids and have their vacations around breaks as well. It would be interesting to see just how these numbers match up. 

3/24/15 - Today I came across a visual cheat sheet to some graphing parameters in R (http://flowingdata.com/2015/03/17/r-cheat-sheet-for-graphical-parameters/). It helps you visualize what each parameter does to a graph, so I thought it would be useful to record and keep track of. It may come in handy later. Pictures and definitely better than words when it comes to visualizing things.