Section 002, Instructor: Larry Dignan

Weekly Question #5: Complete by March 6, 2017

Leave your response as a comment on this post by the beginning of class on March 6, 2017. Remember, it only needs to be three or four sentences. For these weekly questions, I’m mainly interested in your opinions, not so much particular “facts” from the class!

Here is the question:

Just like you did about a month ago, find another online article dated within last two weeks from a credible source that has something to do with data and is interesting and relevant to you. Copy and paste the URL directly into your response followed by a few sentences that explain what is interesting about it.

38 Responses to Weekly Question #5: Complete by March 6, 2017

  • Profile photo of Sarah Linebaugh

    Yesterday, Antonio Brown, of the Pittsburgh Steelers, was named the highest paid wide receiver in NFL history. This article uses a data set to break down how well Brown performed at the NFL combine, which will be occurring this week in Indianapolis. Brown participated in the combine in 2010 and was in the 30th percentile for wide receivers in his 40 yard dash, but was average or below average for the rest of the events of the combine. Brown was drafted by Pittsburgh in the 6th round of the draft because of his underwhelming performance at the combine and being an undersized wide receiver. However, on the field, Brown has very few noticeable weaknesses, which is why the Steelers organization was willing to invest so much money in this diamond in the rough. I find it interesting that more and more data is proving the NFL combine to more obsolete.


    This article is about how to gather all of the data needed to enable self driving cars to be able to go anywhere they want. The self driving car concept cannot go national unless the companies create a map of the United States that includes stop signs, red/green lights, turns, etc. A camera and radar are not enough to tell the car important details like where to stop. This was made clear when the Tesla that Joshua Brown was killed in while it drove in autopilot hit a truck that the autopilot mistook for an overpass. The solution is to crowdsource–have many people drive with cameras on their cars to capture the surroundings of the road. This is interesting because it gives us information about how to gather a bunch of data and turn it into helpful information.

  • Profile photo of Aviva Muskin
    The effects of cardio (specifically Pilates) were tested in this study on the elderly to see if there is an increase in balance, strength, and flexibility. The study was done over a period of 8 weeks, where 10 volunteers exercised 60 minutes a day, three times a week. After each session, balance tests were done to measure the affects of the program. It was found that the program significantly improved the balance of the participants, and resulted in fewer falling incidents. As a music future therapist working with the elderly, seeing the affects of movement and body exercises will change my session plans to include more movement.

    This article talks about how data and visualization were used to measure “depressing music”. In an attempt to answer the question:” What does sadness sound like?”, data analyst Charles Thompson produced a data-driven visualization of the degree to which each of Radiohead’s nine albums are depressing. Thompson used two metrics for his analysis: music and words. For music, he pulled data from Spotify’s API which measure positive and negative response, a music property known as “valence”. For words, he looked for keywords in the song lyrics using data from the online lyrics vault Genius, which had been analyzed and associated with sadness. The results show two clear winners for Radiohead’s saddest and happiest songs, and the data Thompson used allowed him to chart a basic path through the band’s discography, mapping each album by its overall atmosphere of gloom.

  • Profile photo of Calloway F Hatcher

    I love to watch college basketball, especially rivalry games and during March Madness. One of the best rivalries in the history of college basketball is between the University of North Carolina at Chapel Hill and Duke University, which happens to be later tonight. They have faced each other 174 times since 1950, the second most ever during that span, and is among the most even split with UNC winning 93 and Duke winning 81. Overall, with the game coming on later tonight, they will have played each other 244 times. The two schools are also the 16th closest pair of schools, only 10 miles apart, outside of universities in the same city. Out of the 843 rivalry rankings, this one ranks 2nd in total games played, 30th in proximity, and 155th in evenness. When taking into account of the massive number of games played between the schools, and the majority of them both being ranked in the top 25 during the games, it is definitely one of the best, if not the best, college basketball rivalry in history.

  • Profile photo of Imani West

    The article above displays the results of the NFL Combine 2017, which took place on March 3rd. I typically don’t watch this part of football because I don’t know many of the players, but since going to Temple, I was looking out for the few players expected to participate in this year’s combine to watch their performances. The data in the article includes: the player’s name, school, 40 yrd dash time, and their bench, vertical, and broad. This type of data is necessary to help decide who the NFL will choose for their draft picks.

  • Profile photo of Danielle N Buerger

    I found this article interesting because it takes a very popular topic on the news right now that is confusing to a lot of people and breaks it down using data visualizations to help readers better understand what areas of the United States would be affected most by Trump’s new gas and oil regulations. It maps out geographically where the most oil rich areas of the US are and where oil production is growing fastest. This article also directly compares natural gas to oil in all visualizations.

  • Profile photo of Logan J Peterson

    This article discusses the world’s predicament of storing all the data we now collect. In the last two years, the article notes that humans have collected more data than in all of the preceding human history. However, since 2012, data scientists have been storing data in a nontraditional way… embedded into DNA. A single gram of DNA can store 1.28 petabytes of data. DNA also does not degrade over time like cassettes and traditional hard drives. I think it’s fascinating to talk about the long term challenges facing the amount of data we collect. It’s a real problem, but it is good to know there are smart minds already working on the issue. One idea not addressed in the article that I would be interested in hearing more about is the environmental impacts of storing data within DNA. Do DNA data storage facilities require less energy? Are they cheaper or more expensive to maintain? Hopefully these questions will also be worked out as research in this space evolves.


    This article talks about the usage of big data in modern companies and how important it is quickly becoming. I agree with this standpoint because from simply working at an internship I developed and understanding of how important data is in order to predict future trends and conduct meaningful analysis. I think going forward every company will have a heavier reliance on big data since thats where the trend is pointing to now. Big data will help boost intelligence of market segments and customer targets. Overall it will be very difficult to ensure growth and success without big data

    This article talks about satellites that track storms from space. An instrument on the satellite tracks lightning strikes during the storm. This satellite can better help scientists use the data to predict weather patterns including the strength of storms during certain times and temperatures.

  • Profile photo of Yixuan Zhou
    This is a cool data visualization GIFs that can get message across pretty quickly. It shows political polarization in the American public from 1994 to 2015. This form of data visualization is interesting and make audience easy to remember. I actually do not care this topic at all, but the way of representing attracted me. So I think if every storyteller can make their data vivid like this, data science will never a boring subject.

    I recently got a new rifle from my grandfather and so I decided to look up the ballistics of of the round and compare it to others that I am more familiar with. The chart includes velocity, energy, and trajectory. In addition, they include the data for each category relative to distance. The data given ranges begin with the muzzle, then skip every 100 yards until the furthest distance tested at 500 yards.

  • Profile photo of Kalifala Ahamed Konneh

    This article on the New York Times about the U.S. Labor, Housing Markets Data Underscores Economy’s Stamina. I found this article interesting because discuss how data about the housing market, where prices are showing steady and stable growth, indicate stamina and resiliency in employment within our economy. This is interesting to me because it makes me curious as to the direction of causation. Do these two things really affect each other and can we make inferences of employment activity simply based on housing market growth. Just because the housing market is strong does not necessarily mean it is because of strength in employment or vice versa. A top segment of people could simply be doing well and investing in more homes, or developers could be buying properties in bulk. These two things, to me, do not exactly seem to have direct causation, and I would like to look at the data to check it out.

  • Profile photo of Nicolas Patino

    As someone considering an MIS major and future in the data science industry, this article put together a majority of the information I have been looking for, including a beautiful infographic. The most interesting part for me was the stat that most data scienctists (92%) have an advanced degree and 48% obtained a PhD. I enjoyed reading repeatedly that now is a great time to enter this young field.


    This article breaks down betting odds for fights at the most recent UFC event. It compares fighter’s odds and stats in order to analyze who are the best picks to make. The key is to pick underdogs that have good chances and fights that are more likely to end early.

  • Profile photo of Yaning Wang (Will)
    This article talks about how big data now can affect every business in 4 ways. I found this article interesting because how big data can impact a business inside/outside their business and a lot of business do not realize that. Every business can gather data and have access to different types of data, and this can be an asset for the business. Because companies can rely on big data to learn more customer insights, and then improve customer experience. Companies also can use big data to improve their internal performance by analyzing data for each transaction process as well as use big data to find out more information about what makes a good CEO for HR.

  • Profile photo of Benjamin Bucceri

    This article talks about the rising threat of personal information loss through data leaks and how users can protect themselves from falling victim to it. The California based company Cloudware had data leaked from their servers this past week and anyone who has account information with Yelp, Uber, OKCupid and other companies should change their passwords for those accounts. The article then goes on to list the ways users can help protect themselves from data losses through strengthening of their passwords. These tips include: two factor authentication, choosing passwords 8-10 words in length and never duplicating passwords.


    I typically do not watch the NFL combine, but because I got so into Temple Football and their standings/rankings, I thought to actually watch it , especially when 4 Temple Football players went to the combine. When I googled for combine results and I saw the chart on this website, I really liked it. It gives you all the results for many, including Temple’s alumni’s stats.

  • Profile photo of Raymond Wu
    This article is about countries in the United Kingdom that is starting to issue tougher penalties for people that are caught using their cellphones while driving. The penalties may include: twice as many penalty points and increased fines. The article then shows a bar graph that shows the percentage of road users who support a zero tolerance approach to drivers and the UK comes out on top with over 60%. And in another bar graph it shows the percentage of people who admitted to using the phone while driving and UK is the lowest among the other countries. Although the UK has the highest rate of support for a zero tolerance approach, the UK still had over 20% of their drivers admitting to using the phone while driving..

  • Profile photo of Dylan Pesce
    This article explains how big data will evolve over the next three years. Data at its current state is sufficient in making business decisions; however, the lack of depth relative to what it may be in the next few years causes managers and higher ups to make malignant decisions. Data today is often misinterpreted and overvalued without looking at biases and inconsistencies. Big data in the future will be much more in depth and hopefully more accurate in terms of nullifying inconsistencies and outliers.

  • Profile photo of Qing Fei
    This article is about a new marketing strategy of Fitbit. Fitbit was only used to track how many steps the wearers walk every day, but now the company intends to track the wearers’ sleeping quality. The company collects the data of the users’ sleeping time, and wants to provide sleeping tracker to its customers. Because the market of Fitbit is approching saturation, the company tries to add new functions to the Fitbit to attracting more customers.

  • Profile photo of Jason Himes
    This article is about a company which specializes in interconnecting devices to extrapolate data. Because data is useful in nearly every facet of our lives they see being able to take data from nearly everything as a good way to improve things. One example given in the article is that they could use energy output data to tell if a wind turbine may be damaged due to a lower than average output. I think that this kind of use of “big data” definitely has its uses in the world, however I do find it frightening that nearly everything we do is being recorded and can be used by others.

  • Profile photo of Jillian M Foster
    This article is about Data Quality. This is very important to anyone in the world that uses data. If you have bad data, it is not going to get you anywhere. This article talks about 5 important steps when finding data with good quality. You want data to be organized and have the best quality. You can to continue analyzing and improving your data until it can get you the most accurate data possible.

  • Profile photo of Benjamin Paxton Salzer
    As a huge fan of college basketball (and a good friend who is a crazy duke basketball fan) this article was very interesting because it was able to quantify something that many people only judge qualitatively: a rivalry. While it is very easy to just throw out the term, FiveThirtyEight had to, as always, attempt to quantify exactly what a rivalry was. This writer specifically chose to categorize a rivalry as two teams playing each other at least every other year over the last five years, and then broke it down by each team’s national ranking and then by how close the overall series score was. Duke and UNC, as was previously expected, was near the top in almost every category. They are both always good, nearly identical records against one another, close in proximity, and played the most games of any rivalry close to the top, by far. This was a really cool example of how data can verify an age old story.

    The article may not give the image of dealing with data but if Julio Jones gets surgery on his foot, it can impact the fantasy world. Fantasy football is almost all data if not all about data. Data plays a huge role in determining who to draft. If Julio Jones get surgery that can extremely impact his data, a.k.a fantasy points. This will give other wide receivers a chance to boost their data. It’s interesting because I am a huge Fantasy player each year and I have drafted Julio before so this will impact my draft. The article sums up his career and says what is at risk with the surgery and fantasy football.

  • Profile photo of Michael Emmett Fitzpatrick
    This article is essentially an argument that the Federal Reserve’s approach to inflation is too narrow. To predict inflation, the Fed uses a model that looks at labor market slack and inflation expectations. The authors argue that the Fed should use other data in their models to predict inflation. Inflation, the authors find, is highly persistent and not as sensitive to labor market slack or inflation expectations as once thought. The article provides a data visualization that shows trend inflation over the past 25 years. It shows that predicting inflation is actually more accurate when basing it off of the long-term trend line than it is when using traditional inflation models (that use labor market slack and inflation expectations). This article is interesting because it looks at very basic data and points to something very obvious (inflation follows its long-term trend). This is interesting because this prediction method is sometimes more accurate than the current Fed models.

  • Profile photo of Man Shu Wong
    The article is about a recent cyber attack on the 911 emergency call center. During the cyber attack, at least a dozen U.S states were affected by the “largest-ever cyberattack” on the country emergency-response systems. Apparently, the 911 system is vulnerable to hackers, and the reason is that since 2015 there was no budget spent on the cyber security. It is worrisome that how weak the system is and you do not want it to be easily hacked.

    This article is about the new Philly budget presented by Mayor Kenney. It talks about taxes and job creation and fixing up neighborhoods. However, I wonder which part of this budget goes to philly schools. I work for a social service agency that contracts with the school district to provide services to students in the schools, and I shake my head at the conditions of some of the schools, its teachers, it’s resources, it’s lack of staff, everything. So it will be interesting to see how this budget will dispersed

  • This article is about the role big data and artificial intelligence will play in our future. Every year we double the amount the data produced. It is estimated that 10 years from now we will double the data produced every 12 hours. With all that big data, companies will try to make a big sum of money off of it. Soon everything we own will be “smart,” we already have smart phones and are working to towards smart houses, and in the future potentially smart cities and smart factories. But this is not only related to our consumer life but the actual way we live our lives. Some insurance companies are already handing out smart fitness bracelets to increase exercise. Singapore is facing a data-controlled society issue. The program was started to protect the citizens and ended up influencing economic and immigration policy.

    I found this article extremely interesting because it talked about how data was used in the recent presidential campaign, perhaps in unethical ways, and how the company that performed this data research and analytics,Cambridge Analytica, may have breached UK law by reporting on third party data information to guide Leave.EU without the consent of that third party. It was also very interesting to find out how many members of the Trump administration either work/have worked for that data analytics company, or have employed the work of the company. The company admitted to speaking with Leave.EU about the possibility of collaboration, but that was never followed through with. It’s important that the possible negatives that derive from big data and open data be considered as equally as all the benefits it offers, as can be seen in its use to unethically push a political agenda.

  • Profile photo of Patrick Granquist

    There is a new “smart condom” on the market that can track your data in the sheets. The i.Con is a ring that you put over a regular condom and can track anything from thrust count, velocity, temperature, and can even tell you if you are at risk for chlamydia or syphilis. I am curious as to see if the i.Con will become the next big thing. I guess there is a way to find data for almost everything nowadays.

  • Profile photo of Rhea R Prabhu

    The article uses polling data to determine whether the travel ban that Trump instituted is as unpopular as the media portrayal of it on different media stations (i.e. CBS). It concludes that the sentiment towards the ban is something that will require time to unravel. The shifts in opinion on the polls is not significant enough to determine either way.

  • Profile photo of Kush Patel

    this article is interesting because it talks about how in a few years almost all companies will be a part of the cloud. It says how all the companies are switching over because of the amount of data being generated. Another reason they are switching over is because the cloud makes it possible for there to be less hands on equipment and easier online network.


    “Feeling Lonely? Too Much Time On Social Media May Be Why”

    I found this article on my Twitter feed this morning (oh, the irony). I’ve read a lot about the negative effects of social media lately (the “highlight reel” effect and unhealthy comparisons, “FOMO”, etc) but had yet to see any substantial evidence supporting these claims. It’s interesting how tools designed to connect us are actually doing just the opposite. We’ve created a new social currency of “likes” and “follows”, but these things are digital, and not tangible or wholly social in person-to-person contact.
    This is something I’ve especially been considering (and somewhat struggling with) over the past month. I recently took over all marketing efforts for a local company, and I’ve found that I am spending much more time looking at a screen than I am interacting with people face-to-face– even when I am off the clock and out with friends. I’d be curious to see what the data would show for a similar study that focused on people working in communications, whose professional lives depend heavily on social media use.

  • Profile photo of Kush Patel

    This article is interesting because it talks about how companies are beginning to move to the cloud. This means less hands on equipment and more online data processing. This will also be an easier method to store information because companies can use the cloud providers to help them with any problems that come up.

  • Profile photo of Daishaun L Grimes
    This article is about the Migos who are a rap group that are extremely popular right now, and have the number 1 album in 2017. The fast upcoming of a new style of Hip-hop music has the migos at the top of the charts, selling over 200,000 albums in about 3 weeks. This article is important to me because music is very important to society

    A programmer was given a task to organize a concert with zero knowledge in who are good picks. Exhausting all of his contacts with zero result, he crawled musician followings inside the SoundCloud search API. Populating a list through a recursive algorithm and filtering his results through a SQL query, he had the data he needed. All thing left was to make sense of the data through a program similar to Tableau. From there he could easily see up and coming artist who are loved by the San Francisco community.

  • Profile photo of Michael Walsh

    This article is interesting to me because of how the sports world is controlled by numbers. Data is everything in sports because it helps predicting the future, which is what sports teams want most. Data reveal so much therefore making it extremely valuable despite it being such a high risk low reward system.

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