Section 003, Instructor: Ermira Zifla

Weekly Question #2: Complete by February 3, 2017

Leave your response as a comment on this post by the beginning of class on February 3, 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!

If you sign in using your AccessNet ID and password you won’t have to fill in the name, email and captcha fields when you leave your comment.

Here is the question (well, it’s not really a question):

Find a online article dated within last two weeks from a credible source that has something to do with data. It can be about the role of data or an interesting data-driven analysis. It should also be relevant to your major and of interest to you. Copy and paste the URL directly into your response followed by a few sentences that explain what is interesting about it.

You can use any of the sources under the “Great Data Sites” menu on the right sidebar of this page, or you can use any online news or magazine site.

35 Responses to Weekly Question #2: Complete by February 3, 2017

  • Profile photo of James Dean

    http://www.jdsupra.com/legalnews/cyber-ecurity-recent-developments-in-21890/

    This site has a lot of great information regarding recent developments in cyber security relating to financial data. The one entry on the site states that FINRA (Financial Industry Regulatory Agency) fined 12 brokerage firms $14.4 million for violating federal security laws and rules. The firms failed to store records and communications in the WORM (write once, read many) file format. There is another report on there about how they are planning to improve cyber risk management standards for large interconnected financial firms in our country. I am glad to see that the agencies overseeing cyber-security at financial institutions are staying diligent protecting this data from threats.

  • http://www.dataversity.net/the-power-of-data-intermediaries/
    This article included information about how data can be used in a grocery store. The author claims that there needs to be a system of data intermediary in grocery stores. This will help the store by providing access to all of the enterprise data without worrying what systems they come from or where they are stored. The author claims that his will benefit the companies and make them more productive. I am undeclared as a fox student but I found this article interesting because I work in a grocery store part time.

  • https://martechtoday.com/how-data-technology-affect-marketing-2017-194216
    This article entails of how the fields of data technology will merge in the upcoming year, as well as future. I find this interesting because a long time ago, the average person thought of these as two separate fields, but now with our society evolving, we see marketing’s dependence on data technology for success. The article even mentions the necessity of collaborations between Chief Marketing Officers and Chief Information Officers. This was validating for me to hear because I have a strong interest in both marketing and tech, and I now look forward to where my future in both fields will take me.

  • http://journalofbigdata.springeropen.com/articles/10.1186/s40537-017-0063-x
    I chose this site because it relates to my area of interest and major, Media Studies and Production. It provides an interesting view of social media through data as well as a more detailed explanation of Big Social Data concepts. I found this article really interesting because it talks about a topic that concerns all of use and are using constantly, it talks about social and computer-mediated communication through the use of Big Social Data and it is said to constitute approximately 95% of all Big Data establishing a relationship between big data and my major of interest.

  • http://www.latimes.com/nation/la-fg-refugees-screening-20170129-story.html

    This article describes how data is used for the current ban on refugees and the screening procedures. To be determined if an individual qualifies to be considered a refugee, there is an interview (a type of data collection), and other forms of data collection such as identity documents, photographs, fingerprint screenings, security checks, medical screenings, and personal and background information which are a part of the refugee screening process. Also, even after the individuals are in the United States, they are constantly being run through databases to check for threatening information and collecting data on their employment statistics. This is interesting to me because of Trump’s new executive order on refugees, and it is a very good example of how data is used in real-life and in ways that I hadn’t necessarily thought of before. I am currently a Human Development and Community Engagement major so the information and inclusion/ban of refugees affects our various communities and how we interact with and understand others.

  • http://www.jdsupra.com/legalnews/eeoc-releases-2016-enforcement-data-50013/
    The article talks about the Fiscal Year 2016 Enforcement and Litigation Data that released by the U.S.Equal Employment Opportunity Commission(EEOC) On January 18, 2017. The data showed on this article tells the rising number of discrimination charges and monetary awards. The reason why I chose this article is I’m a international student who major in business. Knowing the monetary awards help me to update the information about economy. At the same time, since I’m from another country, discrimination is part of my life. It affects my life perpetually when it goes to a company, when people from other countries are trying to get in a American company. Therefore, I think this is a article that shows useful information to me.

  • http://www.journalofaccountancy.com/issues/2017/jan/general-ledger-data-mining.html
    This article involves data mining with accounting general ledger spreadsheets in Excel. This article was interesting to me because in the accounting profession, we can use data analysis in order to better understand our company’s transaction history and operations. This information can be used to make better business decisions that could help increase profit and decrease costs. I was interested because i want to be able to use the knowledge of data analytics to help my career as an accountant to help other businesses make better decisions.

  • http://www.politico.com/story/2017/01/cabinet-heads-responsible-cyber-data-234431

    In the ‘Trump to make Cabinet heads responsible for data security’ article by Eric Geller, from Politico, Geller informs the reader’s of Trump’s plan to appoint Cabinet officials, and not their lower level staff. Usually, these data obligations are given to that of data information officers of the government, but instead, a senior officer of Trump’s administration was quoted saying, “What we’re doing moving forward is attempting to make the agency heads aware that they have a deep responsibility here.” Now while this article is not highly scientific or number heavy in any type of way, its’ focus on the current event and the irony intertwined in it is what is essential here. Understand that the same administration in which is appointing officials to be head of our nation’s data is also the same one’s in which was elected due to Russian interference, i.e., altered voter’s data. This is also the same administration in which the president harped over inauguration attendance and television ratings, i.e. more data related pools. This is also the same administration in which the president, a well known business tycoon, is likely to be well aware of stocks and other data involving his former businesses or any endeavors associated with him or those around him, his very involvement in the slightest, in any world except the oval office could very well be a conflict of interest. So when it comes to data, Trump’s involvement in such is somewhat ironic. How convenient that a man with interest such as his own has the privilege to hand pick his officials and those that will cater towards his needs. As data is all around us, we must also consider who and how it is being manipulated and controlled.

  • Profile photo of Seth Keatley

    http://fortune.com/2017/01/22/climate-data-trump-admin-hackers/
    This article discusses the efforts that are underway to secure data collected by U.S. government agencies (EPA, and NOAA) in order to prevent its destruction under trumps administration. Some data regarding the climate has already been destroyed under the orders of the Canadian PM. The race against the government to store the data is truly interesting albeit somewhat scary.

  • Profile photo of Luke Greenley

    http://motherboard.vice.com/read/big-data-cambridge-analytica-brexit-trump
    The article I found was interesting to me as it relates to recent major political stories from around the world, but specifically in the United States. The focus was the dangers of big data and the sheer power and influence it possesses. Specifically, the main subject of the article was a company called Cambridge Analytica. This was the company behind the online campaign of two major events in the recent past, Brexit and the election of Donald Trump. Cambridge Analytica is a Big Data company, and they utilize big data statistics for political purposes. The whole process started when a man named Michal Kosinski attended Cambridge University for his PhD. There, he learned of a process called Psychometrics. The process focuses on recording psychological traits of individuals, and from these measurements they can determine someones personality traits, or how they are likely to respond to certain statements. It started as a personality questionnaire app that allowed respondents to share their results on Facebook. However, more applications were discovered for the technique. Soon, the method was being used to target specific voter bases for votes such as Brexit and the 2016 Presidential Election. The company Cambridge Analytica eventually used the method to target certain voters who would likely support Hillary Clinton, and fed them statements over social media platforms such as Facebook that aimed at getting the voters upset with Clinton and suppressing their vote for their candidate. With this system in place, Trump gained an advantage and eventually went on to win. The article highlights a very powerful method of using Big Data, and shows that data can truly change the world when used in a certain way.

  • Profile photo of Parth B Patel

    http://overflow.solutions/interactive-visualizations/when-people-move-out-of-state-what-states-do-they-move-to/

    This was a really interesting article that I found just doing my regular browsing on reddit. The is a much less an article but more of a picture in the form of an interactive visualisation. The visualisation lets you pick a state and see where the people moving out of that state move to. It uses U.S. Census Bureau data to sum up the and relate people moving from one state to another. Just from a basic stand point this is very interesting. Looking deeper as our class readings state this can help bring forth more qualitative insights or theories.

  • Profile photo of Walter Kirby

    http://fivethirtyeight.com/features/under-a-new-system-clinton-could-have-won-the-popular-vote-by-5-points-and-still-lost/

    This was a really interesting article to me because the past few months have been controversial about how Donald Trump did not win the popular vote. It has come up even more frequently in recent weeks as Trump has taken office and made some questionable decisions in office. However, under a new system of electoral college, Hillary Clinton could have won the popular vote by five percentage points but still have lost the election. In order for Clinton to have one, many states would have had to switch their voting to the way Nebraska and Maine does it, with congressional districts being split up. Very interesting for people interested in politics, like myself, as well as people who believe the electoral college is ridiculously (also me).

  • Profile photo of Keerthana Rachamadugu

    http://www.infoworld.com/article/3161222/analytics/getting-off-the-data-treadmill.html
    This article explains how many business just use analytic tools and draw connections between different sectors of their business from these tools. Mintz describes that how that method does not show why certain connections happen making them realize that you have to go back to the workbook stage to figure out the meaning of the data all over again, causing this thread mill effect. The author makes a vague statement by saying, “It’s much less about incorporating the latest machine learning algorithm that delivers a 3% improvement in behavioral prediction, and more about the seemingly simple task of putting the right information in front of the right person at the right time”. Although it seems easy to say its the simple task of putting the right information in front of the right person at the right time, that is a vague statement that doesn’t give much information on how to achieve it.

  • https://fivethirtyeight.com/features/nba-players-can-go-home-again-but-the-ticket-moochers-will-be-waiting/

    I found a very interesting article on the data site thirtyfiveeight that talks about one of the newest and most popular trends going on in the NBA currently. This trend is about how many veterans in the NBA have returned to their hometown teams to play ball whether it be by trade or being signed through free agency. The article has two forms of data that show this trend. One is a chart that shows the percentage of players playing in their hometowns from 1988 up until the present day and it proved that more players are playing in their hometowns this year then any other year. This is as important as it is interesting because if more players are going home, this likely means that ticket sales will continue to rise because it is generally perceived that fans want to watch players who are from the actual area. I would expect ticket sales and NBA popularity to rise if this trend continues.

  • https://www.entrepreneur.com/native/n?prx_t=nY8CA8lAMAMxcNA
    This article explains how data and analytics will transform the customer experience. In the article it says that times are changing and if you want to reach your customers on a different level then you need to expand your social network. They are trying to create a more personal experience because everyone wants to feel special. Also you can see what the people want if you allow them to leave feedback. I think companies and organizations should care about their costumers because if they didn’t have costumers, they wouldn’t have the company.

  • Profile photo of Johnny Luu

    https://www.theguardian.com/sport/2016/aug/04/finland-tops-podium-for-most-olympic-medals-won-per-capita

    This article stated that the country of Finland won the mot Olympic medals per capita. They have about 2.30 medals per million of people in their population. They came to this conclusion by taking the total number of medals won divided by the number of summer Olympics competed in.This article was interesting to me because when you think of Olympic medals you’d only think of who won the most overall not how many were won per the people that country. Even though this is a random fact it is still interesting nonetheless.

  • The article I found discusses a newly discovered email phishing scam. The scammers send practicing accountants an email that states that information was stolen from user’s electronic services accounts in 2015, so they need to update their accounts to ensure their information is secured. When clicking the provided link the practitioner is led to a website that has the official IRS logo and the official e-services registrations page. The goal of this scam was to obtain usernames and passwords to the official IRS website as well as personal information for malicious purposes. This article is interesting to me since the scammers were able to fabricate the official logo, which made this scam all the more effective. My major is accounting so knowing how to identify scam websites will be important to protect myself from identify theft.

  • In relation to my Major of Sport and Rec Management, I decided to take an article off of ESPN that relates to certain sets of stats that may leave the Cleveland Cavaliers regretting ever making the trade and getting rid of Andrew Wiggins. On a recent hot streak, Wiggins has been averaging nearly 28.8 points in the last four meetings against the Cavaliers, being a bit of a problem. In the NBA data set, Wiggins rates 77th of 79th among Power Forwards in the League, which is surprising for a player with his talent. Last season, he was in the 25th ranking among all players. To drop 52 places in one season is significant, but to have a four good games in the past against the team that traded him, is even more impressive.

  • Profile photo of Kahleem M Wilkins

    http://www.infoworld.com/article/3164249/artificial-intelligence/new-big-data-tools-for-machine-learning-spring-from-home-of-spark-and-mesos.html

    This articles talks about how “Big Data” can help improve machine learning. AMPLab was created with “a vision of understanding how machines and people could come together to process or to address problems in data.” That could mean more accurate predictions by machines which will in turn relieve some analytical responsibilities from humans.

  • Profile photo of Alison Kline

    https://www.nytimes.com/reuters/2017/02/01/business/01reuters-usa-economy.html?_r=0

    This article describes data that proves that the national factory activity has increased to a level higher than it has been at in the past two years. This increase in factory activity indicates an expansion in manufacturing which accounts for 12% of the U.S. economy. The data of the index came from the Institute for Supply Management(ISM)’s production index. ISM is a source of great interest to me as I am a Supply Chain Management major and ISM will help me throughout my supply chain career. This article is very intriguing because it describes the impact the economy can have on aspects of the supply chain, like the fact that the increase in manufacturing came with an increase in both quantity of orders and prices of raw materials which I will have to understand and adjust for in my career when I may need to procure those raw materials or facilitate those orders.

  • https://bdataanalytics.biomedcentral.com/articles/10.1186/s41044-016-0018-9

    This article is about how sentiment analysis is becoming a more useful tool in the world of marketing and commerce. It explains how the academic research groups are becoming more interested in this method of analysis and continuously attempting to develop learning techniques for language processing and many other fields. Experts have found that collecting data from sentiment analysis has become a conundrum; however the layout for sentiment analysis enables them to create new solutions for the future!

  • https://www.nytimes.com/2017/02/02/education/edlife/will-you-graduate-ask-big-data.html?_r=0
    This article dissects the theory given by Georgia State University that if a student fails or comes close to failing a introductory course or foundation course, it is likely that that student would not graduate. The stats showed, if a nursing student was on the bubble of passing their math course as a freshman, by junior and senior year they were doing very poorly in everything. This would lead to now having to go into more debt to take a 5th or 6th year of college or completely dropping out. This is interesting because this can apply to all college students, if I’m failing all of my core classes most related to my degree, statistics show I may not even graduate. Pretty scary stuff.

  • http://www.journalism.org/2017/01/18/trump-clinton-voters-divided-in-their-main-source-for-election-news/

    This article came from the Pew Research Center and it discusses the various media outlets that people who voted in the 2016 election got their information from. The data here interests me because you can see a clear polarization when looking up news on certain candidates. By far the most interesting thing I saw was that the media outlet with the third highest percentage was Facebook, which isn’t a news sight at all. The second most interesting thing I found was that 40% of Trump supporters used Fox news as a source. I feel like this data can be best used to show the polarization of American voters, but I also think it shows WHAT is causing the polarization and can maybe provide ideas on how to solve it.

  • Profile photo of Dong Choe

    http://www.cnbc.com/2017/02/02/snap-ipo-s-1-filing.html

    Snapchat is very well known app with more than 100 million downloads. This extreme successful private company has filed for an IPO, initial public offering. This means that snapchat is no longer a private company but will be able to be owned by share holders or at least a percentage. Snapchat requires an active phone number and contacts syncing them with your phone and others to have this huge database of exchange messages via video, images, and text.

  • Profile photo of Jibreel Murray

    https://www.bloomberg.com/news/articles/2017-02-02/factory-skills-gap-could-spell-trouble-for-trump-s-jobs-plan
    This article is interesting data-driven analysis regarding the US job market under Trump’s Administration and if their plan to bring back US factory jobs can be successful. The data shows that there are 340,000 possible manufacturing job openings this year alone. The skill gap is one large factor standing in the way of Americans and nearly 340,000 factory jobs. Today’s labor market has about a 43 Percent talent scarcity. While the data shows that the tech force is almost single-handedly offsetting the skill gap. Factory workers are still left out of the loop as Large manufacturing companies look give jobs to robots. Trump and his Administration now face the task of getting manufacturing companies back to America and having them employ humans.

  • https://www.wired.com/2017/02/police-get-location-data-without-warrant-end/
    In this Wired article, it is described that in many states (33) there is no protection against a third party (cell phone provider) giving the location of the customer away to the police, in fact, sometimes a cell phone provider generates revenue from selling information, “any are offering a range of surveillance techniques to law enforcement for a fee, including text and call tracing and cell phone location services.”.
    This raises the question: would a cell phone provider gain more revenue if they promised its customers that they would be protected?
    “Privacy regulations haven’t kept pace with the advancements we’ve made.”. As a reaction, Texas and New Mexico are taking steps to ensure that under the ‘third party’ clause a cell phone provider does not overstep what many see as right protected under the fourth amendment.

  • Profile photo of Moeed Faisal

    http://overflow.solutions/demographic-data/what-states-have-the-most-people-that-are-foreign-born/

    My little data snippet is on the states that have the most foreign born residents. As a future actuary, I’d probably be taking this information into account when thinking about product sales or insurance premium pricing. This also confirms my expectation that California and New York would have the highest number of foreign born residents although I didn’t think that California would beat New York by the percentage it did. This may also be relevant to current events in regards to Trump’s foreign policy moves.

  • Profile photo of Robin Goetz

    https://fivethirtyeight.com/features/trump-could-really-mess-up-mexicos-economy/
    This article by Lucia He, which was published on fivethirtyeight.com, describes the negative influence of Donald Trump’s Anti-Mexiko way of politics. It uses analyzed data starting from the time he first introduced these ideas in his candidacy for president of the United States until today. The author makes clear, based on economic data from the Mexican government and the WTO, that Mexico depends on the US as an important source of income, e.g. money flowing back from Mexican, who emigrated to the US and now support their families, but also makes clear that both countries profit from the free trade they were having. Trump’s anti-mexican campaign would therefore hit Mexico very hard, which can already be seen by data and the projections of experts, like those of the Mexican bank Banamex, but would also hurt the US in the long run.
    The article does a great job to support its arguments with the use of recent data from credible sources and therefore is very interesting for me, as that is what I am trying to learn – finding useful information in a big set of data.

  • Profile photo of Amy Huynh

    http://www.forbes.com/sites/bernardmarr/2017/02/01/what-really-happens-to-your-big-data-after-you-die/2/#147894a82577

    This article explains to readers what happens to their big data after they die. The article breaks down the aftermath of various data such as digital collections and medical data once you have passed away. The title of the article sucked me into reading this article; it intrigued me because I never really thought about what happens to my different accounts on websites, medical records, etc. when I am no longer living. Something I found interesting while reading this is that your medical data could potentially be accessible even after your records are destroyed – some of your data could be used for statistics reporting and research. Although your data is anonymized when it reaches to this extent, it’s still out there for the public to see, and this could be seen as a problem to some people.

  • https://www.wsj.com/articles/snap-lists-sustaining-user-growth-as-one-of-its-biggest-risk-1486075541
    The app Snapchat, available for both iOS and Android systems, recently disclosed that one of its biggest business concerns currently is maintaining user growth. If the amount of new users and current users decreases, Snapchat’s business will be negatively affected. The company’s main concern now is to keep the current users (mostly teens and millenials,) engaged and entertained In order to remain successful, Snapchat has decided to file an IPO so that the company will now have public shareholders. While this is good for the company, going public could potentially affect the user base and experience. There is also the worry that after the recent inauguration, at some point in the future, restrictions and regulations will be put in place that could also affect the company.

  • Profile photo of Memoona J Khan

    https://www.theguardian.com/technology/2017/feb/02/snapchat-evan-spiegel-growth-facebook-ipo-analysis
    This article gives insight on how Snapchat is growing rapidly and about to reaching the level of facebook. Since the release of Snapchat, it has become popular among a specific age-group, mostly between ages 18-35, which have been the main app users. It’s main issue has been how to continue to grow, attract more users, and keep it unique without having to change its goals.

  • Profile photo of Emma Girandola

    https://fivethirtyeight.com/features/trump-could-really-mess-up-mexicos-economy/

    Due to Trump’s proposed policies, Mexico’s economy is already taking a beating and is expected to fall even more if these policies really start. Following Trump’s first press conference after the presidential election the Mexican currency fell to $21.91 pesos to the U.S. dollar. The more he threatens to put his policies into play and build the wall the more companies and individuals cut back on spending. Consequently hurting the economy even more because there is less money that is being circulated throughout the market.

  • Profile photo of Sarah Trested

    https://fivethirtyeight.com/features/stop-saying-trumps-win-had-nothing-to-do-with-economics/
    This article discusses economics and its relationship with politics and the recent election. In the past, many people voted for the candidate with economics being the voters top priority. However, measures of racism and sexism, and markers of social status such as a college degree, did a much better job predicting whom voters would support for this election. The data collected for this article includes information about unemployment rates, voter turnout, who voters voted for this year compared to who they voted for in previous elections, among others.

  • Profile photo of Patrick Murt

    http://www.networkworld.com/article/3160132/application-development/want-to-be-a-software-developer-time-to-learn-ai-and-data-science.html
    The article I read, which was titled “Want to be a software developer? Time to learn AI and data science”, discusses the evolving demand for a variety of skills in the software industry, especially Artificial Intelligence (AI) and Data Science. As AI continues to incorporate itself into more and more things that we use throughout our daily lives, like cars, we can see a larger demand for people with the skill and knowledge necessary to perform in the job market for software engineering. With the larger demand for AI familiarity, this also requires much knowledge with Data Science, which is crucial to understanding how AI actually works.

  • Profile photo of Jordan Massey

    http://venturebeat.com/2017/01/31/pandora-billboard-hot-100/

    The article talks about the inclusion of Pandora’s streaming data as one of the streaming services that is being used as a determinant along with physical sales and radio airplay for the Billboard Hot 100 list. The reason Pandora is now being included with streaming giants like Soundcloud and Apple Music is because its has gained more users and influenced how Billboard’s charts are being tabulated.

  • https://www.theatlantic.com/education/archive/2017/02/the-ivy-leagues-gender-pay-gap-problem/515382/
    The article I chose utilized data to analyze the earning disparity in median income of men and women who graduated from ivy league schools. I found the article interesting both as an economics major and in general. The author of the article also referenced studies and analysts from economics professors at Harvard and the University of Chicago, to which the conclusion was reached that personal choices being made namely by women are what are responsible for the disparity in median income. Although, some interesting insights can be found. If a women has a high earning spouse she tends to make less in her field. This is because ivy league schools are some of the largest exporters of financial workers and consultants, jobs that require unmitigated dedication due to their inflexible hours. The conclusion follows that once a women has a child she has to quit these jobs since part-time work in not an option, and because her spouse is a higher earner she is the one who takes responsibility of primary child care.

  • https://www.wsj.com/articles/stocks-seek-direction-as-political-risk-counters-positive-data-1486096662
    This article exemplifies the, often interesting, speculative role of data in financial markets across the world. Efficient financial markets are known for their ability to process new information into the pricing of the market, so US economic data, like the first jobs report of the year to be released this Friday, is of great concern to many investors. Often, investors will even use data about the US economy to predict metrics about upcoming economic data, and the speculation about unreleased data is watched closely in markets all over the world. This article also demonstrates the point that data is not isolated from news and other information in the decision-making process. Although the upcoming jobs report data is predicted to be objectively positive, the current political risk of the economy has deflated the positive pricing impact of the data.

  • Profile photo of Ellen Gbeyeh Wiah

    http://www.reuters.com/article/us-venturecapital-bigdata-idUSKBN14X24C
    I choose this article because it focuses on the amount of personal information that data company are collecting on people and the risk that comes with it. The article the importance of collecting large amount of data and how collecting big data helps Airbnb’s know whether its customers prefer to travel to the beach or mountains, and Uber knows popular drop-off locations and how to price trips. The article also talks about some of the risk involve in collecting big data and people personal information, for example, in the article Matthew Zeiler, founder and chief executive of Clarifai, a visual recognition tool used in healthcare, talked about creating a Wikipedia-style database of anonymous patient data that was open to the public but Gabriel Otte, founder and CEO of Freenome, a cancer-detection startup argued that, doing that could be harmful to patients.

  • https://motherboard.vice.com/en_us/article/how-our-likes-helped-trump-win
    This article discusses how a psychologist created a tool that can analyze social media users activity to learn demographic details about the person. This tool is a form of psychographics or psychometrics which measures psychological traits like personality. Here is an interesting quote I took from the article: “Remarkably reliable deductions could be drawn from simple online actions. For example, men who “liked” the cosmetics brand MAC were slightly more likely to be gay; one of the best indicators for heterosexuality was “liking” Wu-Tang Clan. Followers of Lady Gaga were most probably extroverts, while those who “liked” philosophy tended to be introverts.”

  • http://www.chicagotribune.com/sports/football/bears/ct-bears-postgame-biggest-plays-htmlstory.html

    This article really interest me, because it’s a data-driven analysis on the Chicago Bears and Minnesota Vikings football game that took place on January 1st, 2017. The Chicago Bears had a very rough season trying to figure out the right quarterback that could be consistent while playing throughout an entire game. The biggest problem that they were having is that they kept turning over the football averaging five turn overs a game; the most in the entire NFL. In this article by the Chicago Tribune, Ryan Marx and Chad Yoder break down the swing momentum in the game that proves that Chicago couldn’t be their best at the biggest parts of the game, which led them to a 3-13 season. In the chart that Marx and Yoder display its shows that the Bears turned the ball over 7 times, in each of those 7 times prior to the turn over the win probability was extremely higher. After every turn over we saw an extreme decrease in the chart.

Leave a Reply

Your email address will not be published. Required fields are marked *

Office Hours
Ermira Zifla (instructor) 10:00am-12:00pm Wednesdays, Speakman Hall 207C or by appointment.
ITA
Prince Patel (ITA) by appointment only. Email: tug04032@temple.edu
Subscribe to Blog via Email

Enter your email address to subscribe to this blog and receive notifications of new posts by email.

Join 20 other subscribers