Section 006, Instructor: Shana Pote

Weekly Question #5: Complete by October 12, 2016

Leave your response as a comment on this post by the beginning of class on October 12, 2016. 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.

30 Responses to Weekly Question #5: Complete by October 12, 2016

  • An article that I found interesting was on Guardian Data Blog. The article collected all the data about natural disasters and when they occurred. Also, it uses the data to compare countries to see which one is the safest and riskiest place to live. The article uses data visualizations by using bubbles and color schemes to make it easy for the reader to understand the concept of what the data is for. This caught my attention since currently hurricane Matthew is happening and is on its way to Florida. https://www.theguardian.com/global-development/datablog/2016/apr/25/where-is-the-riskiest-place-to-live-floods-storms

  • I found my article on The Atlantic website. It’s about how a Stanford professor set out to create an algorithm to predict the best-seller-chance of a new novel. As someone who loves reading, I found it cool how someone could map out something as complex as a novel into numbers and patterns that could then be computed in an algorithm. I agree with the creator that the algorithm would, of course, not replace the human “gut instinct” of publishers. While many patterns can be deduced and analyzed, no model is ever 100% correct. Human judgement would still be needed to supplement any factors the algorithm would miss or possibly identify outlier best sellers that the mass public would like. But this is a great example of how data can be used on non-numerical subjects and still manage to help the industry. In this case, the algorithm could help draw more attention to would-be-best-sellers.

    http://www.theatlantic.com/technology/archive/2016/09/bestseller-ometer/499256/

  • I found this article on FiveThirtyEight. I decided to explore political side because I realized I have not shown enough interest in related topics. The article i found is on the Obamacare law.It explains how the law has increased insurance coverage all over the country. The article first of all cites the beginning of this years election when most of the primary election candidates adopted this law as campaign point. The fact that this stopped towards the ending of the election helps me to understand that the positive effects of this law have started to increase. the article also uses effective data visualization to hep me understand at a glance that the number of people who are uninsured have reduced in states all over the country. I think the reason the candidates have stopped mentioning Obamacare in their campaigns is that they see that it will make substantial changes to the insurance coverage rate in the country. Because that was what i could evaluate just from the data visualization provided.
    http://fivethirtyeight.com/features/obamacare-has-increased-insurance-coverage-everywhere/

  • The article i found was on FiveThirtyEight. This article talks about the Obamacare law and how it has improved the health care insurance coverage in the united states. At first there was a negative reaction to the establishment of this law, which is why many of the primary election candidates used it as a campaign point at the beginning of this years election. this article uses an effective data visualization to help me understand, at a glace, the reduction of the number of uninsured people in states all over the country. I think it is safe to draw that from the data representation, there will still be a further reduction in the future, which is the reason why candidates are no longer talking about this in their campaigns.
    http://fivethirtyeight.com/features/obamacare-has-increased-insurance-coverage-everywhere/

  • The article I chose for this question was from FiveThirtyEight. The article is titled “How Many Times Did Trump Interrupt Clinton In The First Debate? Depends On How You Count”, I wanted to use this article for my explanation because I feel it has to do a lot with bad data and how it can be caused. This article was about the differentiation of the interruption count. Different media outlets all had different numbers comparably. We see this bias in numbers because there is not an exact definition of “interruptions” for every reporter/viewer of the presidential debate to go off of.

    http://fivethirtyeight.com/features/how-many-times-did-trump-interrupt-clinton-in-the-first-debate-depends-on-how-you-count/

  • An article that I found interesting and cites many sources of data is Nate Silver’s article on FiveThirtyEight about the affects of the recently discovered controversial recording of Donald Trump on his chances of winning the election. I find the article interesting because I think that the presidential election of 2016 itself is very scandalous and filled with controversies. Silver’s article cites nine polls that have conducted interviews since the tape’s release. Silver then writes about the affects of sampling error with respect to Trump’s ratings. Some polls show that Trump’s ratings had not changed, while other polls show a huge change. I find it interesting that different samples of voters can yield a wide arrange of results, especially in the context of something as large as the presidential election.

    http://fivethirtyeight.com/features/election-update-polls-show-potential-fallout-from-trump-tape/?ex_cid=2016-forecast

  • The article that I found is on Forbes’ website and is about how big data is helping us to predict almost everything imaginable. I think that it’s really fascinating how we are able to use big data to make predictions and use those predictions to identify future potential problems and therefore potential solutions to those problems. For example, big data is allowing us to make predictions in high school graduation rates and then find ways to attempt to keep students in school. I think that this is very interesting because of how it will help us in the future to further develop society and become more knowledgeable and intelligent as people.

    http://www.forbes.com/sites/bernardmarr/2016/10/10/5-amazing-things-big-data-helps-us-to-predict-now-plus-whats-on-the-horizon/#12e542ad2b63

  • The article that I found is on Forbes’ website and is about how big data is helping us to predict almost everything imaginable. I think that it’s really fascinating how we are able to use big data to make predictions and use those predictions to identify future potential problems and therefore potential solutions to those problems. For example, big data is allowing us to make predictions in high school graduation rates and then find ways to attempt to keep students in school. I think that this is very interesting because of how it will help us in the future to further develop society and become more knowledgeable and intelligent as people.
    http://www.forbes.com/sites/bernardmarr/2016/10/10/5-amazing-things-big-data-helps-us-to-predict-now-plus-whats-on-the-horizon/#12e542ad2b63

  • After surfing around the web for a little, I came across an article on Forbes that discussed why analytic investments have yet to pay of for companies using such methods to earn a profit. The article went into depth as to how companies are struggling to find a positive correlation between data analytics and making the right business decisions in regards to making investments. However, the author clears the air a little bit when he explains that its not necessarily the data analytics that are causing a lack of success, but rather human error in how to properly understand and navigate such resources. To make things more comprehendible, the author breaks down as to why these issues are occurring into three defined reasons. The reasons as to why there is a lack of success, is due to the lack of communication between business leaders and analytics, how analytics is implemented in the business’s operations, and having the correct platform to perform such actions. I found this article interesting, because as a business major, data science is becoming an integral part to attaining success in the business world. If one could bridge this gap between data analytics and profitable investments, the possibilities are endless.

    Link to article:http://www.forbes.com/sites/bernardmarr/2016/06/27/why-investments-in-big-data-and-analytics-are-not-yet-paying-off/#eb3829280a25

  • The article that I found interesting was “Rangers And Jays Battle To The Postseason’s Most Exciting Game- So Far” on FiveThirtyEight.com. The article ranks the MLB playoff games by the “Excitement Index,” which estimates how likely each team is to win the game at any given moment, based on how they’ve done historically in similar situations. The index was originally used for basketball, but has been transformed for the baseball playoffs. The “exciting games” feature large swings in the win probability for each team, with the probability changing after each play such as a strikeout or a home run.

    http://fivethirtyeight.com/features/rangers-and-jays-battle-to-the-postseasons-most-exciting-game-so-far/

  • The article that I found interesting was off of the five thirty eight website and it was a article about the poll information that is found in the polls in relation to the current election. The main focus of the article is centered around the fallout cause by the trump tape that was released to the public. In the tape Donald tape is making disrespectful comments about female. The article show me the different changing in Donald’s ratings people that were once for him have change there mind because those comments he made. http://fivethirtyeight.com/features/election-update-polls-show-potential-fallout-from-trump-tape/

  • The article that I found interesting and relevant was one on Amazon, and how they plan to implement their grocery/food section of amazon into real stores. In this article, Amazon states their data about how they plan on making a series of corner stores around the country that focus on selling fresh groceries. However, this is not what the most exciting part! They also plan to have drive through spots at these corner store locations, where people driving home from work can just drive through, pick up what they need, and go home! There wouldn’t be a need to get out of the car after a long day of work to go shopping! Amazon is trying to turn their digital data world into real life which is amazing to see! I love Amazon and shop on there all of the time, that is why I found this very interesting and relevant for myself.

    https://www.theguardian.com/technology/2016/oct/11/amazon-grocery-stores-food-drive-through-jeff-bezos

  • http://www.espn.com/nfl/statistics/player/_/stat/rushing/sort/rushingYards/year/2016/seasontype/2

    This is a list of the NFL rushing leaders since as of week 5 of the 2016 season. It contains data such as yards, attempts, yards per attempt average, touchdowns, fumbles ect. All of this is data that has been compiled from each game. It is interesting and relevant because these stats can tell you who is the best players this year, who is most valuable, who deserves a bigger contract and even more. It is interesting because it not only tells you who is good but it also has financial implications.

  • The article I found interesting is titled, “2016 Election Forecast,” and it uses poll data to show the change in projected electoral and popular vote and subsequently chances of winning for each candidate. The accompanying map (to the data) shows the breakdown of popular and electoral votes for each candidate by state and is color coded red (for Clinton) and blue ( for Trump). The most recent aggregation of data reveals that there Hilary Clinton has an 86.3% chance of winning and Donald Trump has a 16.4% chance of winning. This information is useful, however, I think being able to see the changes in the three aforementioned fields (electoral, popular and chances of winning) over time is particularly insightful. It shows the impact of debates/media stories, etc. The map graph and line chart included are both very easy to read and make picking up data easy. The upcoming election is an important event with outreaching impacts, so it is covered by every news outlet. The graphs and polls on each network is different, so it is nice to use a credible data source to see an accumulation of polls in one place.

    http://projects.fivethirtyeight.com/2016-election-forecast/?ex_cid=rrpromo

  • http://fivethirtyeight.com/features/election-update-women-are-defeating-donald-trump/
    The data driven article I found interesting for this week pertains to the apparent gender gap in candidate preference that is showing itself in the current election going on. FiveThirtyEight explores hypothetical scenarios about election outcomes if only one gender were voting for each candidate. The article showcases the obvious data that backs up the statement of Clinton’s very wide margin of women voters as opposed to Trumps margin of mens voters. One interesting point noted in the article was that if men were the only ones voting, Trump would win essentially anything considered a swing state across the electorate map. The purpose of this article is to mainly highlight how polarized the overall electorate has become and how changing demographics has caused a substantial shift in how some candidates are received.

  • The article I chose was “Hurricane Matthew’s US death toll rises to 33 as flooding chaos continues” which is found on the Guardian Data Blog. I always like to stay up to date with current events. This event is especially relevant to me as I am from Florida and all of my friends go to school back home. I kept up to date with this hurricane and kept in touch with my family and friends to make sure everyone was okay. Unfortunately, the new information from this article shows that 33 people have died because of Hurricane Matthew. Although it’s sad to read about, I think it is important to stay up to date with current events.

    https://www.theguardian.com/world/2016/oct/11/hurricane-matthew-death-toll-shooting-north-carolina-florida-georgia

  • I choose an article (or rather a video) on CNN that talks about a platform called “Prism” that can track shoppers’ movement in a store using the security camera to help retailers understand their customer behaviors. We live in the age when e-commerce businesses are booming thanks to the Internet. Because online shopping allows retailers to track customers’ shopping routines and recommend items based on the data they have, online shopping became a much more convenient and effective way to shop for both retailers and customers. However, the Prism platform can now bring this online tracking technology to physical stores. By using security camera to capture shoppers’ movement inside the shop: which direction they go, what they touched, which corner attract them the most, etc, a heat map that shows the ‘traffic’ inside a shop is generated to help retailers analyse their business and create a better shopping experience for their customers, like how they are able to do it online.

    http://money.cnn.com/video/technology/2016/08/15/shopping-tracking-technology.cnnmoney/index.html?sr=recirc101116shoppingtechnology1030vid

  • I chose an article that predicts the likelihood of each baseball team that is participating in the post season this year. The article outdated now because it’s a week old but I chose it out of spite because they gave the Giants a 3% chance of winning the world series. The article ranks the teams with a scoring system used by fivethirtyeight that gives points to teams according to a myriad of factors. It sorts the teams according to their general ability and performance with the most well rounded teams at the top and the teams that have had the most shaky seasons at the bottom.
    http://fivethirtyeight.com/features/major-league-baseball-is-about-to-get-random/

  • I choose the article named ‘The End Of A Republican Party’ that discuss about Election2016, which is one of the most important events in these days. The article used data to analysis characters of GOP and showed the overall characters of GOP are whiter, older and less educated. Then tables shows the division within the party. People like or dislike Trump in GOP hold different views. This is interesting is that through the data and data visualization we can know who in GOP are and what views they actually hold. That can helps us know Election2016 more deeply.
    http://fivethirtyeight.com/features/the-end-of-a-republican-party/

  • The article I choose is from FiveThirtyEight. It is about how to measure the Hurricane Matthew, which is the strongest and wired wind since it is not close enough to make an landfall.The author, Eric Holthaus, thought speed itself cannot be used as the only way to measure this hurricane.Besides, storm surge,size and track also need to be thought about when estimate danger to people and property. This inspires me that when we collect the data,we must think about all the possibilities and cannot limit on just a few number of datas.

  • The article I found is from the journal of accountancy and it discusses retirement fears of Americans. Forty-one percent of CPA’s reported their clients’ number one concern is running out of money for retirement. This is because the baby boomer generation has been tasked with not only supporting their children, but their elderly parents as well. The elderly are living longer than once projected, which is causing them to run out of the money they had previously saved. I find this interesting because as an accounting student and hopeful future CPA, knowing what people are concerned about and how to help them with it will assist me in the future if I choose to open my own practice.

    http://www.journalofaccountancy.com/news/2016/oct/americans-fear-running-out-of-retirement-money-201615242.html

  • I choose an article titled “A Handful Of Cities Are Driving 2016’s Rise In Murders”, an issue that is a big talking point in today’s presidential election. The author Jeff Asher took data provided by the FBI to highlight the rise in crime rates compared to last year, and while the rate has been rising it seems to only be concentrated around big cities such as Chicago, Orlando and Huston. Due to this distinction found by Asher it lets us know that although the data shows the crime rate increasing, it is important to know how the statisticians arrived at this conclusion. The article shows that one must do a little deeper research into the content they find online to prove its insights and get a better understanding into the facts and figures.

  • The article I found was about the Chicago Cubs and how everyone projected them as number 1 all year long. The 2016 Cubs were compared to many great teams like 1927 New York Yankees and the current Golden State Warriors. But why is everyone so hot on the Cubs, is it because of there hot start? There ELO rankings put them at the top of every other team. The ELO rankings are the projections for the year, so from winning the division to bringing home a World Series and the Cubs sit at 1582. The next team below them is 17 points below at 1555 which are the Toronto Bluejays still maybe not a big number to some but in sports that is a pretty big margin. They have this much confidence from everyone even with there 108 year old World Series drought. With 103 victories the last team to do that was the 2009 New York Yankees, who went on to win the title that year. The Cubs outlook looks bright in October.

  • The article that I found interesting delved into the benefits of extracting data from the human genome to find patterns that help explain what causes certain viruses. In particular, this article looked at two major viruses that have plagued our population over the last few years, such as Zika and Ebola. This case interviews Pardis Sabeti, who is a computational geneticist at MIT. Ultimately, his lab is data-mining the human genome for cures. http://www.wired.co.uk/article/genetics-viruses-ebola-zika-tick

  • An article which I found interesting came from The Guardian Data Blog. The main premise of the article is to illustrate to society how the U.S. Government spends money in the 2016 federal budget. The data is presented in an interactive way that adjusts the amount of tax by category depending upon total income. The reader simply drags the bar according to their annual income which corresponds to the amount of tax per government spending area. This is an extremely effective way of illustrating data to a wide audience.

  • The article I choose is called “Chinese Public Sees More Powerful Role in World, Names U.S. as Top Threat”. There is no denying that China has been expanding their power inward and outward. They grow stronger economically and politically. But how do the citizens think about this trend? What does the world think about the trend? It’s interesting to find that, under the leading of President Xi Jinping, Chinese see their global role expanding, but most are wary and looking inward. The concern of food safety and medicine safety has also aroused in the recent years. The article talks about different aspects and the data shows what the Chinese and the world responds. Although President Xi Jinping may not make any difference in his decisions upon these data, it’s still a very interesting collection of responses to read into.
    http://www.pewglobal.org/2016/10/05/chinese-public-sees-more-powerful-role-in-world-names-u-s-as-top-threat/

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