Section 001, Instructor: Laurel Miller

Weekly Question #5: Complete by March 2, 2017

Leave your response as a comment on this post by the beginning of class on March 2, 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.

59 Responses to Weekly Question #5: Complete by March 2, 2017

  • https://www.washingtonpost.com/graphics/national/united-states-of-oil/
    This article is interesting to me because I’ve taken a couple courses relating to fracking and how horrible it is to those living near these sites and to the earth itself, however majority of U.S citizens benefits from cheap oil and gas and the US in general makes a lot of money. In this website, it shows how there’s an increase in U.S oil/gas. It contains colorful graphs that shows the increase in oil.gas and color maps that shows where these gas/pol sites are and labels describing them.
    To know that “there are more than 900,000 active oil and gas wells in the United States, and more than 130,000 have been drilled since 2010” and for Trump to lift more bans is pretty devastating to those living near these sites and to the earth itself. I believe that there are better alternatives than to dig up the earth for gas/oil or money.

  • https://fivethirtyeight.com/features/would-trumps-blue-lives-matter-effort-really-help-protect-police/
    This article takes a look at President Trump’s signed executive order to try to make attacks on police a federal crime. The article takes a look at the numbers behind cop deaths to see whether this would truly have an impact and protect cops. Behind the numbers, the highest cause of death for a police officer between 2011 and 2015 on average was traffic-related, which makes the proposed changes, not necessarily effective, as traffic-related deaths are accidental, and the order won’t do anything for accidental deaths. The article was interesting, because the way the media frames attacks on police officers, you would think law enforcement deaths would be on the rise, however, according to the article, they have been on a downward trend for overall for years. Hopefully something can be done to effectively protect police officers, as I am a strong supporter of law enforcement.

  • http://www.usatoday.com/story/tech/nation-now/2017/02/15/switch-worlds-largest-data-center-building-opens-nev/97967578/
    This article talks about the creation of the world’s largest data center building in Reno. The magnitude of 1.3 million square feet area for data is pretty insane and commendable. This means more data can be stored in our every expanding world of data. On the plus side, the facility runs off of renewable energy and can help provide faster data speeds to the surrounding area.

  • https://www.forbes.com/sites/bernardmarr/2017/02/22/big-data-why-nasa-can-now-visualize-its-lessons-learned/#1835c6672003
    This article is extremely interesting to me due to the relevance of NASA right now, and how critical data is to the operations of them. The way they use data and programs that sort through millions of documents is amazing. The way Meza used a database to determine that the data sorting program was not efficient shows how important data can be. Mesa also mentions how he found a program that makes it easier to combine information and showcase it in a graph form. This is relevant because we are using Tableau to showcase information just as NASA is using a program that does just the same called Neo4J.

  • https://www.bloomberg.com/view/articles/2017-02-16/do-you-trust-big-data-try-googling-the-holocaust

    This article is talking about trusting the big data you see. Lots of data now a days is not filtered or changed frequently. In the article, Mr. O’Neil states “When I typed the phrase “Was the Hol” into Google, the search engine auto-completed to “Was the Holocaust real?” Of the top six search results, four were Holocaust-denying sites. That’s despite Google’s efforts to address this problem back in December, and I’m not unique.” This was one of the few examples he used in the article to show that big data isn’t always reliable.

  • https://www.forbes.com/sites/quora/2017/02/06/is-data-science-too-easy/#2030f97292a9

    I found this article interesting because it discusses data scientists in the current professional climate and offers insights about the occupation. The article goes on to explain the role of a data scientist and how they contribute to the field of data science with the utilization of technologies like R and Hadoop. It also points out that data science is a growing field and no company is certain about the “right” way to go about analyzing Big Data. Overall, it is clear that the job is difficult, but successful data scientists are extremely valuable to an organization.

  • The title of the article is “More Than Half Of Age Data In Mobile Exchanges Is Inaccurate” and it’s written by Allison Schiff. The content of the article as a whole was surprising to me. For starters, Schiff states that most of the available age data on mobile exchanges are inaccurate. While it is common knowledge that the open exchange is known to have some inaccurate data, it’s still astonishing to see some of these numbers. Age is one of the primary pillars of demographic data, but “72% of requests on ad exchanges do not include age data” and “when ages are associated, 60% of that data is inaccurate.” Age is a crucial targeting parameter and if the inaccurate data is used, it could completely destroy a marketer’s campaign. I’m further curious as to why most requests on ad exchanges do not include age data. Perhaps marketers are smart enough to know where to request age data. If not, however, I have to ask why wouldn’t they request age data, as it is as important a parameter as gender.
    URL: https://adexchanger.com/data-exchanges/half-age-data-mobile-exchanges-inaccurate/

  • URL: http://www.dataversity.net/fascinating-artificial-intelligence-story-robot-boss/

    The title of this article is “An Artificial Intelligence Story: The Robot Boss and Data Operations” and it is about artificial intelligence and a robot called the “Robot Boss”. The article talks about how the robot boss can replace managers in the workforce today by using past data to allocate employees to work in the most efficient manner and also it can evaluate new work by using data on work processes to boost efficiency and production. This article was interesting to me because lI like to learn and read about AI and how it can improve businesses or people’s lives. Also, the article was interesting because this is not something that is on its way, it has already been implemented in Japan and it has been proven that the robot boss does boost productivity.

  • Source: http://money.cnn.com/2017/02/25/technology/data-refuge-saving-data/
    Data Refuge is a volunteer group of hackers, scientists, writers and students. Their main goal is to preserve the collected federal data and keep it publicly accessible. The group found that the White House has removed all federal data from the site. The site now only displays a message informing the searchers to check back soon for new data. Data such as animal testing, puppy mill cruelty and company audits were completely removed since the inauguration of Trump. The spokeswoman for the USDA informed CNNTech that the removal was done to protect privacy. The removal of public data affects many organizations since they are dependent upon the data. In order to prevent data droughts, Data Refuge has participated in civic activism to prevent such scenario from taking place.

  • Source: https://www.forbes.com/sites/danielrunde/2017/02/25/the-data-revolution-in-developing-countries-has-a-long-way-to-go/#31962b291bfc

    The article discusses how it is essential for countries and their governments to acquire accurate data, such as birth/death rates, crime rates, weather patterns, demographics, etc. As countries become more democratic and rich, societies show interest in investing more money to improve data acquisition mediums. However, the collection of actionable data in developing countries is difficult and expensive. The author gives the example of Myanmar, a country that has suffered through long periods of conflict. Although they have developed over the years, the government collects data on paper in the form of spreadsheets, which is an outdated form of collecting information. The article states that in Myanmar, only 1 in 30 civil workers has access to computers; such countries can only gain some data from “remote sensors, cell phones, satellite information and digitizing information”. Regardless, the main concern is that people in such countries must not only have access to computers and the internet, but also need basic mathematical and analytical skills. Even if the data is collected successfully, there are two major issues: “politicization of data” and privacy. I found this article very intriguing as I was not aware of the issues that the less developed countries are facing when it comes to data acquisition, and this is something that is not discussed very extensively on the public platform. Hopefully, the launch of the Global Partnership for Sustainable Development Data (GPSDD), formed by the United Nations, resolves these difficulties faced by the developing world.

  • Source: http://www.rdmag.com/article/2017/02/sports-equipment-sensors-send-data-directly-coachs-smartphones

    This article about the installment of sensors into sports equipment interests me because of the direct effect it can have on sports at all levels. These low cost sensors can help athletes improve their skills by measuring things like speed and trajectory. They also could help officials make accurate calls on a professional level. For example, a touch sensor could tell NBA officials who last touched a basketball before it went out of bounds. I think this is great for athletes, coaches, and sports in general, as the data derived from these sensors can help athletes of the future on all levels improve their skills.

  • http://mashable.com/2017/02/23/elon-musk-tesla-lifetime-insurance/#JmslVnabYkqQ In this article, Tesla is beginning to be so sure of its self-driving car that the company is going to offer lifetime insurance and a maintenance program. This means that those monthly bills are gone and a peace of mind could start to set in. I find this most interesting because the technology came so far since the debut of the first Tesla to even mention something like a lifetime insurance.

  • https://www.forbes.com/sites/valleyvoices/2016/01/20/five-ways-data-analytics-will-shape-business-sports-and-politics-in-2016/#5f57c74169be

    In this article, data analytics is becoming the next big thing for the 5 major sectors of business. The business insurance industry are collecting lots of new data to see if any new major trends are happening. They want to start serving the older babyboomer generation. There is a huge amount of them who do not have nay kind of life insurance and people want to start seeing to get them into getting insured. They said it is never to late for them to get it.

  • https://fivethirtyeight.com/features/mars-needs-lawyers/

    In this article, data is analyzed for future costs to get humans Mars. In 1989, NASA estimated a future 400 billion dollar human Mars mission…that number in 2014, turned out to only be a mere 100 billion. Today it is reported that numbers are as low as just 6 billion dollars. The article describes how the mission is so expensive that it is not talked about in the media much at all anymore.

  • https://fivethirtyeight.com/features/trumpbeat-is-trump-already-messing-with-government-data/

    I found this article interesting because it discussed how data can be abused to sway opinions and further personal agendas. By manipulating data so that it fits with a conclusion a certain party believes in instead of using data to form conclusions, people can use data to persuade others into supporting their views. This is particularly dangerous when the data in question is government data. When important government data is manipulated or removed, there is a lack of knowledge necessary in order for the public to form their own unbiased opinions.

  • https://www.orbitmedia.com/blog/blogger-research/
    I am interested in blogging (or any type of lifestyle online resource)e being apart of my future career. In this data set, Andy Crestodina asked 1075 bloggers the same 11 questions and came up with some helpful insight of successful bloggers. For instance, to the question “how long does it take to write a typical blog post” they found most bloggers take 1-2 hours. And to the question, “Do bloggers use editors?” they found most bloggers edit their own work. Crestodina basically found that bloggers are doing more than before in regards to their blogs. It’s interesting for me to read how successful bloggers handle their blogs, so I can use this as a helpful starting point.

  • https://phys.org/news/2017-02-smart-analysis-stuttgart.html

    I found this article very interesting because it showed me how our mobile network connects us all.This article specifically talks about how our mobile network is a possible solution to help with traffic in cities. This is a very good idea and analysis if you read the article because it shows that open data has many applications to creating a better and more efficient society.

  • http://www.baselinemag.com/analytics-big-data/how-to-get-business-value-from-big-data-analytics.html

    I selected this article because it provided more insight into big data and its role within a competitive business landscape. The article discusses how IT is becoming a commodity amongst businesses, specifically with the IoT. According to the article, 65% of IT leaders believe that that they risk becoming irrelevant and/or uncompetitive if they do not embrace big data, while 64 percent say that big data is changing traditional boundaries and 24 percent are already experiencing ingress of competitors from adjacent sectors. The three key areas where business leaders are focusing on within this space is: infrastructure, the IT framework to support data, and the individuals in the organization. This enables the ability to identify the most relevant data out of a broader data pool.

  • http://www.biztechmagazine.com/article/2015/07/golf-gets-swing-analytics

    This article relates to me as I have a passion for golf as well as the drive to continuously getting better each year. Analytics in golf have made tremendous improvements over recent years as they can now fine detail almost every aspect of the golf swing. The article is interesting to me as I can so closely relate to some of the same work professional are doing that I also do in my free time. Often my coach can simply throw numbers at me about say the loft or swing angle and instantly I know where I need to adjust.

  • https://www.theguardian.com/film/datablog/2016/aug/19/thirty-years-of-pixar-from-toy-story-to-finding-dory-the-studios-biggest-hits

    This article really fascinates me because I’m a big fan of Pixar and animated movie. The thing I love about this article is the data visualization which shows the budget and the profit of movies categorized by topics such as monsters, toys, animals, etc Combine with the bright color which matches with topic of animated movie, audience can easily see what movie brings a lot of profit for Pixar and what categorized movie is more favorable. This data visualization inspires me to think of broader data visualization types in which we can be creative. It also reminds me of the lecture and the readings about data visualization in class. Lastly, it is amazing that Toy Story 3 has the highest profits of more than $860 million!

  • Source: https://fivethirtyeight.com/features/oscars-night-was-predictable-until-the-very-end/
    This article is interesting to me because it shows how predictions of the Oscar awards are made using data. The accuracy of these predictions is really high, 7 out of 8. Analysts forecast the winning movies based on their accomplishments in other awards, and also what other awards previous Oscar-winning movies have received. Using this pattern, they have precisely predicted the winners in best documentary and best-animated feature categories. For the best director category, analysts easily predicted the winner based on the result of the Directors Guild of America Award, as the pattern shows that the Academy usually follows the decision of the DGA. Analysts failed to predict the winner of best picture award, but saying they would make some adjustments to their methods of collecting data which they believe would enhance their prediction accuracy in the future. The story shows me the predictive power of data after a pattern has been discovered.

  • http://www.economist.com/news/finance-and-economics/21717431-bilateral-trade-flow-data-are-misleading-reported-tweak-will-not-help
    This article’s topic is America’s trade imports and exports, and how Donald Trump intends to make changes to the trade policies. It is fascinating because of the various data it presents. Currently, America sells goods to gain trillions of dollars in revenues, thus increasing the the amount of money owed to America by other countries. With Donald Trump’s intended plans, America would lost money in the billions and the trade deficits of other countries would decrease in the billions.

  • http://journals.lww.com/nsca-jscr/Abstract/publishahead/Predictive_Validity_of_National_Basketball.96164.aspx

    This article talks about a study investigating predictive validity on future basketball players entering the NBA Draft Combine. The data gathered consists of a principal component analysis (PCA) and looks at the correlation between first-year on court performance and third-year on court performance. Three components that were identified in this data were length and size, power and quickness, and upper body strength. The common predictor trend that they found for all-star on-court performance at the NBA level was a players length-size. This article is interesting to me as I have been interested on how NBA coaches determine a college players value for the longest time. This article answers my question and the Sixers “Trust the Process” system.

  • http://journals.lww.com/nsca-jscr/Abstract/publishahead/Predictive_Validity_of_National_Basketball.96164.aspx

    This article discusses the predictive validity of the NBA Draft Combine on the future performance of basketball players. The data is gathered by a principal component analysis (PCA) or principal component regression (PCR) that analyzes first-year and third-year on-court performers at the college level. Three components that were identified would be length/size, power/quickness, and upper-body strength. Of the three components, length/size was the predictor that was significantly most associated with future on-court performance at the NBA level. This was interesting to me because I was always wondering how NBA scouts and coaches determined a players value. Now, I understand the Sixers, “Trust the Process” system.

  • Source: https://www.washingtonpost.com/news/wonk/wp/2017/03/01/the-problem-with-trumps-plan-to-boost-wall-street-banks-are-more-profitable-than-ever/?utm_term=.102f1f16f2ac

    As a prospective Finance and MIS major, this article is of great interest to me because it showcases hard data about the profitability of banks and financial institutions since the financial crises. It also talks about how President Donald Trump plans to get rid of certain regulations like Dodd-Frank, that will, in turn, contribute to making big players on wall street even more profitable. The article shows that how the net operating income of most of the banks in the country has been increasing ever since the crises, and how the rate of failures by ‘troubled bank’ has been decreasing. Furthermore, the article gives key insights about the target numbers (in billion and trillions of dollars) banks and financial institutions such as Goldman Sachs and JP MorganChase plan to achieve in the upcoming year. Overall, this articles precisely illustrates all the claims it makes by providing supporting evidence of hard data and infographics.

  • https://www.theguardian.com/technology/2017/feb/28/amazon-web-server-crash-internet-problems
    This article is about how Amazon web servers have experienced an outage for several hours. It is Amazon’s S3 cloud service that has experienced the glitch and caused problems for apps that rely on that cloud service like Medium, Business Insider, Slack, Quora and Giphy. This outage was so bad it even caused a site called “is it down right now?” to even glitch, and this site is supposed to monitor when other sites are down. Some people even rely on these apps or sites to turn on their lights at home, which they couldn’t do because of the outage. The reason this article seemed so interesting to me is because of the fact that I love technology and new things. Things like turning on lights from your phone or computer is my thing, or monitor things anywhere through your phone is cool. So, after I heard about the outage and how some people couldn’t even turn on light, I started to double think these new cools things. I started wondering whether or not these products are even worth it, if they could go through an outage like Amazon’s S3 cloud service outage.

  • https://www.gamblinginsider.com/in-depth/2942/advanced-guard-the-importance-of-data-security
    I believe this article is really relevant because reports the importance of company’s investments in data security in order to avoid bad publicity and lost revenue. Security data breach can have substantial negative impacts on an organization. The author points out five critical levels of security and conclude saying that the best way to protect sensitive gaming data such as customer credit cards, personally identifiable information and player data is to remove as much of the sensitive information from the merchant’s environment in order to not “touch” the merchant’s system and therefore, there is no valuable data to steal. Taking preventive actions like this, the company could avoid negative long-term effects like damage to the brand and loss of trust, loss of customers and negative political implications.

  • http://flowingdata.com/2016/10/31/sentiment-analysis-on-trump-and-clinton-faces-during-debate/
    This article is an analysis of Trump and Clinton’s facial expressions during the first presidential debate. This is interesting to me because I followed the election very closely and have become more into politics because of this crazy election. Although the presidential election had a great affect on our country, I was mostly following it for a source of entertainment, and the dataset I found is the same type of entertainment. It is funny how accurate this analysis is, a good dataset if you want to laugh.

  • http://blogs.wsj.com/cio/2017/02/28/open-data-is-key-to-open-markets-in-era-of-ai/

    This article about the incorporation of Open data with the technological advancement of AI (Artificial Intelligence) is quite intriguing in that it states how the combination of both of the aspects mentioned above can lead to a smarter robotic machine, when compared to an average smart human being. Even though the immediate minimum wage labor affect would be quite negative, the long term affect would be positive overall as the introduction of a new segment in the economy would not only create more jobs for the individuals educated in the sector, but also would create a whole new intriguing field in general. Finally, as we mentioned in class that most high worth companies wish to keep their data private, and don’t wish to share it to the common public. This statement is relevant in this article because the entire premise of this article is to advocate for Open Data, so it can be utilized to its’ potential, to further develop AI, which is not only a promising field but also an emerging one.

  • https://fivethirtyeight.com/features/the-ncaa-is-modernizing-the-way-it-picks-march-madness-teams/

    This article here I thought was very interesting, because it talks about how the NCAA Tournament committee is changing the analyltical system they use to pick what teams do and don’t make the field of 68. Their current system known as RPI (ratings percentage index) was developed in 1980, but after the past couple years of the committee snubbing some teams that by the popular opinion thought should be in, they are introducing new aspects to the system from another index know as KPI(Ken Pom Index) that was developed in 2004 by a Michigan State basketball manager. This is a big deal for me, because I am a HUGE college basketball fan and would like to see the committee be able to better select the right teams to be put in the field. On top of that I am considering to go to graduate school for Sport Analytics, so this article really piqued my interest.

  • https://fivethirtyeight.com/features/when-did-sports-become-so-political/-

    This FiveThirtyEight article is based on the overall significance and correlation between sports and data. Sports history and player comparisons rely strictly on data, the statistics of players to be specific. The article shows how data and statistics are essential in observing and comparing different athletes based on home runs, touchdowns, points, goals, etc. When people say that “data is everywhere”, they truly mean this. Sometimes, I come to forget how important data is to sports. However, sports history and comparisons rely heavily on data.

  • https://www.nytimes.com/2017/02/28/technology/science-research-researchgate-gates-goldman.html?rref=collection%2Fsectioncollection%2Ftechnology&action=click&contentCollection=technology&region=stream&module=stream_unit&version=latest&contentPlacement=10&pgtype=sectionfront&_r=0
    This New York Times article details an open source for researchers to post their papers and get tips from fellow researches on where to focus their time and what will help them. It is essentially a social media network that connects scientific researchers to better assist their data collection. It was solving the problem of slow feedback on current research and a lack of network for researchers to communicate. They have raised $52.6 million from investors to fund this project. They also detail how this type of crowd learning has become more popular, used in cancer research and at Ivy League Universities.

  • https://www.theguardian.com/lifeandstyle/datablog/2016/sep/17/oktoberfest-beer-fried-chicken-rollercoasters-and-more-beer

    This article is about the number of liters drunk by visitors of the 2014 Oktoberfest. A bar graph shows 1980, 1985, 2004, and 2014 numbers of liters drank. It went from only 3.8m liters drank in 1980 up to 7.7m in 2014. There is also a scatter plot showing as the years have increased the price per beer has also went up.

  • http://www.nature.com/news/data-on-movements-of-refugees-and-migrants-are-flawed-1.21568

    The article about data movements of refugees and migrants is interesting because we are aware of the fact that these people are leaving their countries but we are not 100% sure of where they end up going. In Europe, this problem had an enormous impact in terms of which country needed the most help and where exactly. The data is useful to take initiatives to help these people like in Germany. The growing number of immigrant coming into the country was the reason why the german government decided to provide them courses to learn a specific area of the business and contribute to the society. This solution, benefitted both parties.

  • https://thevideoink.com/oscars-predictions-data-on-youtube-says-the-winners-are-f6513d00ab38#.b2dgrbvmi

    With the huge hype and talk about the recent events that occurred which is the Oscars its only fitting bring data relating to Oscar Predictions before the Oscars happened. I like this because it focuses on the biggest areas in which people wanna see in the Oscar predictions and also it’s very straight forward and organize. With one of the graphs it clearly shows the difference between each area of subject just by how large the difference is and which is more soupier then the others.

  • http://quotes.wsj.com/QVCA/financials

    The stock price of a share of stock for QVC was at a high of 26$ one year ago. Since then the price of a share of stock has been showing a natural decreasing trend down to 19$ a share. on august 3rd the stock price of QVC dropped significantly by 6$

  • http://smallbusiness.chron.com/role-data-business-20405.html

    I feel like this article is important because it is relevant to business and in order to have a successful business you need to know your data. If businesses used all of the data they got then that data would benefit them every time. But the problem is about half of the data you get inst need and is useless. I feel like if you mastered analyzing data and you implemented it into your business then your business would be doing much better.

  • URL- https://www.nytimes.com/2017/02/23/nyregion/new-york-city-subway-ridership.html?rref=collection%2Fsectioncollection%2Fnyregion
    This article is about how people in New York City would rather take an uber or other car service rather than the subway. This is the first time the subway ridership has declined in 8 years. The article says that the percentage of people taking a subway on a weekday has increased slightly, but the percentage of people taking a subway on a weekend has gone down, probably due to visitors and people going out. A problem that could arise from this is that the amount of traffic in the city could be even worse, which is hard to believe.

  • http://www.theaustralian.com.au/business/technology/yahoo-ceo-marissa-mayer-to-take-pay-cut-for-data-security-breach/news-story/9ec1ed8eeb23766b171bca8f533f950f

    This article discussed the continuous data breaches that Yahoo has been encountering. It was an interesting read because the article was primarily focusing on the fact that the data breaches are occurring because of the executive team is not putting enough time and care to “properly comprehend or investigate” said breaches. I think this is an important thing to note about companies and their data. Similar to anything in an organization, it starts from the top down. Yahoo’s executives need to take data seriously, especially in the process or protecting it and preventing these breaches from happening again. Without the time and diligence spent on this, these breaches will continue to happen and Yahoo’s reputation will continue to go down. Data is important and executives/CEOs need to make this a priority – especially for a tech company like Yahoo.

  • https://med.stanford.edu/news/all-news/2007/07/music-moves-brain-to-pay-attention-stanford-study-finds.html

    This article is basically about a study that the Stanford University School of Medicine did testing the theory that (classical)music helps us focus. They conducted an experiment that monitored brain activity which showed that the most activity was during the transitions between movements. I thought it was interesting because we’ve all heard that theory growing up, and we’ve all seen pregnant women put headphones on their bellies and it’s just an interesting concept. But what interested me most about the article is that I study classical music and I love the idea that it makes you smarter. Lucky me!

  • URL: https://gcn.com/articles/2017/03/01/nyc-data-pedestrian-safety.aspx

    This article basically talks about how data from car accidents and how people drive can help prevent future accidents from occurring. Some examples given were that some devices record information about how people brake too hard and speed too fast. Using that information, they classify which areas of New York are known for extreme braking and speeding and see if there is a correlation with the number of accidents at those areas. The article also states that because of lack of light in certain areas during winter and fall correlated with a 40% increase in severe crashes. Using this data, more light could be added to prevent fatal accidents. I found this interesting because I was thinking about the amount of money insurance would save when they would have less claims to pay. I take an introduction to risk management course and my professor talks about insurances and how they are not evil and are good for you.

  • https://fivethirtyeight.com/features/russell-westbrook-cant-stop-going-left/
    This article discusses an anomaly about NBA superstar Russell Westbrook’s play this season. Westbrook has been having a phenomenal year, averaging a triple double 60 games into the season (meaning that he has three different statistics in double digits). However, despite his dominant performance, he is being extremely predictable in one-on-one situations this season. The article shows how Westbrook moves to his left nearly 3/4 times and still manages to get around defenders to keep his numbers so high. It’s very interesting to see that even though Westbrook is predictable according to the data yet he still leads the league in scoring. I found this article interesting because I enjoy analyzing sports statistics and have been paying close attention to Westbrook’s historic season.

  • https://www.forbes.com/billionaires/#/version:realtime_page:3

    This artcle is about world’s richest man. The most interesting thing is it changing real time. One week ago, China’s biggest express company came into the market. And the founder became a billionaire. But at that time his net asset was about 1.5 billion. A lot of people want to buy the stock, and now his net assets is 26.7 billion. We saw the whole process his net assets was increased 2 billion per day. Now he is the third richest man in China, 26th in worldwide. I choose it because it is a dynmic data. Everytime we check it, it may have some things different.

  • https://fivethirtyeight.com/features/the-minimum-wage-movement-is-leaving-tipped-workers-behind/
    This article is about the minimum wage of workers that are paid with an actual minimum wage versus the workers who work for a low pay, but gets all the tip money. It talks about how we should help out and tip our serves, because most of the time they do not receive the full minimum wage. I thought it was very interesting to read this article, and they also added in a chart that has a list of all the states with the minimum wage for tipped workers versus general minimum wage.

  • https://fivethirtyeight.com/features/trumpbeat-is-trump-already-messing-with-government-data/

    The article I chose is about Trump’s administration and how there have been talks of the government changing the way that they calculate the trade deficit. I found this article interesting because Trump’s administration is trying to manipulate Census data that people, all around the world, look to. In changing the way the trade deficit is calculated, there will be a bias in the data. Doing this would make the deficit look worse than it really is and help Trump push his (probably outrageous) trade policies.

  • http://www.theverge.com/2017/3/2/14788218/5g-mwc-2017 5G: (Super Fast Data, throttled by reality.)

    I choose this article because it describes how our technology have been advance at such a fast pace. The ability to connect to 5g will revolutionize our connection as a whole. The new speeds will allow users to download at a rate of 10 gigbits per second, which is unheard of! This will allow people to access data quicker and to process it faster. This technology will change the way humans interact and learn.

  • https://projects.fivethirtyeight.com/congress-trump-score/
    This is an interactive data visualization in which you can see how closely each congressman/woman and house representative voted inline with Trump’s policy. If you click on the politicians name you can then see each bill that was voted on in the Senate or House and how each politician voted on that. Then if you click on the hyperlink of each bill it will bring you to Congress’s website going more in depth about the bill. This link gives you information on what party the congressman/woman or representative is, a score on how closely he or she votes in line with Trump’s policy, Trumps share of the election votes in that specific state or district, how often they were predicted to vote in line with Trump, and the difference of their predicted score and actual score.

  • https://fivethirtyeight.com/features/the-minimum-wage-movement-is-leaving-tipped-workers-behind/

    This article discusses how the minimum wage movement seems to be ignoring tipped workers. The data used in the article details the different pay gaps between tipped workers and minimum wage workers in different states. I used to work in a tipping job and I can relate to what the article talks about with how frustrating it could sometimes be when I left the day with an amount less than 7.50 an hour. I hope that both can raise with one another at the same rate in the future so that tipped workers are not left behind.

  • http://flowingdata.com/2016/06/28/distributions-of-annual-income/
    The title of this article is “Shifting Incomes for American Jobs”. The article is very interesting to me because it uses a really good data visualization to display the pattern of amount of income employees have in different eras- the sixties, eighties, 2000, and 2014. It makes sense for the numbers to be what they are before the turn of the century, but it’s interesting to see the comparison from 2000 to 2014. I can also use this graphic to see what my future occupation is likely to make, and the pattern it looks like its moving forward towards. For example, if I wanted to be a technician, there’s a lot better of a chance for me to make a salary over $200k in 2014 than there was in 2000.

  • https://www.forbes.com/sites/kurtbadenhausen/2016/12/06/michael-jordan-heads-the-highest-paid-athletes-of-all-time-with-1-7-billion/#6e5731b91f1d
    The title of this article is “How Michael Jordan heads the highest paid athletes of all time with $ 1.7 billion” written by Kurt Badenhausen. Even though, Michael Jordan the NBA’s greatest player made $93 million in salary over 15 seasons playing for the Bulls and Wizards, he generated $2.8 billion in revenue for Nike in its most recent fiscal year. In this article, he also states the salary for the other athletes who has and had high salary such as Arnold Palmer, Tiger Woods, Michael Schumacher, Nolan Ryan, Roger Federer, Alex Rodriguez, Lionel Messi and etc.

  • http://www.sporttechie.com/2017/02/07/analytics/bigdata/how-data-runs-the-sports-world/
    This article shares information on how big sport data collection is within professional sports. Most fans think that just the statistics and numbers we see on ESPN is the only data analytics professional sports teams do. However, as shown in this article sports organizations do a lot more than that, including, finding out the best times to air the games, customer behavior, how much to price the tickets, etc.

  • https://www.nytimes.com/reuters/2017/02/23/business/23reuters-usa-economy-unemployment.html?_r=0

    This article discusses 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 effect 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.

  • http://www.cnbc.com/2017/02/27/digital-video-game-sales-surge-in-january-to-75-billion.html
    I’m a gamer, and I download the game to PC directly because I don’t like to keep DVDs. In this article, the SuperData Research reports that video games downloaded directly to personal devices increase 9.8% in January compare to the same period last year. Download version sales to PC and consoles raise fast these years. More and more gamers prefer to download at home instead of buy at a store.

  • https://www.mtggoldfish.com/articles/modern-on-sale

    This article discusses the prior and expected future prices of cards from the card game “Magic: The Gathering” based upon an upcoming set of cards. The article draws from data collected over the years, and uses it and past trends withing the data to estimate where the prices will go next, and when the best time to buy certain cards is. This is an interesting topic to me because I play the game, and I will be engaging in the buying and selling that influences the market.

  • https://www.theguardian.com/travel/2015/nov/18/top-10-budget-beach-hotels-mexico-pacific-coast-bed-breakfast
    With spring break just around the corner, many students travel to warmer climates, preferably with beaches. This article names the top 10 cheaper beach hotels on Mexico’s Pacific Coast. All of these hotels stretch along the 1,000 mile coast that is known for it’s fabulous beaches. It states when the hotels were built and how much a stay is per night. With us students being on a tight budget, these hotels are pretty reasonable prices, all located on the beautiful coastline. Mexico is the perfect place for a getaway with friends while escaping the stress and pressures of school work for a week.

  • https://www.forbes.com/sites/bernardmarr/2017/03/01/fake-news-how-big-data-and-ai-can-help/#103448c170d5

    This Forbes article discusses the demise of “real news” especially during an intense period of political change. Seeing the results if Brexit and the U.S. election, many were under the notion that the news being catered to them through sources like, Facebook and Twitter, were true but they were actually “Fake news”. Like big data, it’s hard to fact check everything once it’s out there, but there are many initiatives being created in order to make sure that the honest influences of media, news, and data are being put out, while the others left out.

  • https://dzone.com/articles/big-datas-role-with-connected-cars-and-our-environ

    This article addresses the importance of data collection when creating a better transportation network. With the goal of fully autonomous vehicles at hand a lot needs to be taken in account. Data will shape how these autonomous cars will preform, taking into account much more than a human driver. Using data this pieces of tech could become the most efficient taking in everything from traffic patterns to weather.

  • http://www.zdnet.com/article/cloudbleed-post-mortem-points-no-evidence-of-exploitation/
    This article was interesting because it shows how danger opendata can be. The website used to deliver content called Cloudflare got bugs and its data was leaked. Although it is very private tool for people to use to transfer datas, when It gets leaked it can very dangerous. Similar to the case of Barclays from the reading, people should aware of danders while transfering data to others.

  • https://fivethirtyeight.com/features/lebron-doesnt-get-better-in-the-playoffs-hes-always-this-good/
    This article is relevant to me because im a huge NBA basketball fan and its currently payoffs time. The article talks about how Lebron James doesnt get better in the playoffs, however he is always this dominant. the data table show hoe his player efficiency is almost the same during the regular season as it is during the playoffs. It also compares him alongside all time great players who put up similar stat line.

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Laurel Miller (instructor) 11:00am-12:00pm, Tuesdays and Thursdays, Speakman Hall 210 or by appointment.
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Rebecca Jackson (ITA) By appointment only. Email: rebecca.jackson@temple.edu
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