Section 005, Instructor: Joe Spagnoletti

Weekly Question #8: Complete by April 5, 2017

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

Here is the question:

Once again, 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.

48 Responses to Weekly Question #8: Complete by April 5, 2017

  • http://www.techrepublic.com/article/march-madness-5-data-sources-that-could-predict-the-2017-ncaa-championship/
    I posted this article because I always wondered how it is possible to create a tournament bracket that does not leave me upset. This goes into multiple data sources from different websites that break down what goes into creating a good bracket.

  • https://gma.yahoo.com/police-self-driving-uber-arizona-150458162.html
    This article is interesting from my stand point because I am studying Risk Management and Insurance. Self driving cars are a new loss exposure for insurance companies and this instance with a self-driving Uber car getting into an accident is a perfect example. Insurance companies aren’t quite sure how to price these exposures and how detrimental they are to society. Although this self-driving car was not at fault for this accident, it’s difficult to determine how these cars are programmed to react to situations like being cut off in an intersection.

  • https://fivethirtyeight.com/features/how-the-gop-bill-could-change-health-care-in-8-charts/
    I picked this article because I was not fully aware of how the GOP Bill would affect people under Obamacare. I found the data graphs for representing the impact the bill would have on every segment of Obamacare to be extra helpful when trying to understand it. Overall I found the article to be pretty interesting, easy to follow and relevant to anyone living in the US, as the decision pretty much affects everyone one way or another.

  • https://fivethirtyeight.com/features/nba-teams-are-resting-players-earlier-and-earlier/
    Being a basketball fan, I found this article interesting, but also saddening. In a graph in the article it shows how from the 05′-06′ season up to this current season, NBA coaches have steadily been increasing the number of players not playing in games due to rest. It has at least, tripled since the 05′-06′ season!! I think this makes the game less competitive and less fun to watch, it is really a bad message to the fans.

  • http://dataconomy.com/2016/07/from-shelter-to-forever-home-big-data-helps-pets/

    I googled “dog data” because I really love dogs. The first few articles were about a rude graph rating dogs on a scale when they’re all good. Anyway, this one is about how big data helps shelters figure out where and when animals will be abandoned so they can find them more often. It also helps make marketing more effective so animals can find new owners. I’m a fan of big data now.

  • http://www.espn.com/nba/story/_/page/tripledoubletracker/follow-russell-westbrook-triple-double-chase
    Russell Westbrook is having a historic season. Right now in the league he is averaging a triple double. He is on his way to being the player with the most triple doubles in a season. On this website it shows graphs and charts of how Westbrook is actually doing on his pathway to being the player with the most triple doubles in one season. His triple double count has sky rocketed based on the chart on the website compared to a few years ago to this year. Also his specific stats are compared to Oscar Robertson’s stats for when he became the player with the most triple doubles in one season.

  • http://www.cnbc.com/2016/04/06/big-data-starbucks-knows-how-you-like-your-coffee.html
    This article is about how Starbucks has used consumer data to develop a new line of products including K-cups and ready to drink beverages. They used the data to figure out how people drink their coffee and tea at home and designed products that reflected those preferences. For example, they found that 43% of people do not use sweetener when drinking tea at home, so they developed two unsweetened ice tea K-cups. I found this article interesting because I drink a lot of coffee and tea.

  • https://www.nytimes.com/2017/03/28/magazine/none-of-us-are-safe-from-getting-owned.html?rref=collection%2Fsectioncollection%2Ftechnology&action=click&contentCollection=technology&region=rank&module=package&version=highlights&contentPlacement=1&pgtype=sectionfront
    Oddly enough there is an article about being”OWNED” on New York Times Magazine. This article illustrates the increasing level of threats and vulnerability we are exposed to as technology advances over time. This raises many concerns as what you have on your labtop/desktop or phone can be accessed without you even knowing. Someone could potentially own all of your data including , search history, pictures(naughty or nice), documents, contracts, basically your entire life. With exposure this threatening we might all want o invest in some protection at the least.

  • Here is the article that I found interesting when I read it: http://www.pewresearch.org/fact-tank/2017/02/15/u-s-students-internationally-math-science/. The article basically gives me the general information about how well American students do in certain subjects in schools comparing to other students from other countries. The article also includes the bar chart which shows the average math, reading, and science score of the test that many students from a lot of countries took. Surprisingly, students in Singapore have the highest average score in all three subjects. And there are 17 countries have a significant higher score than the U.S in science, 35 countries have a significant higher score than the U.S in math, and 14 countries have a significant higher score than the U.S in reading.

  • http://flowingdata.com/2017/04/04/visual-simulations-to-show-uber-game-strategies/
    The article I chose is Visual Simulations to show Uber game strategies which was posted on April 4,2017. I thought the most interesting fact about this article is how Uber company encourages drivers to work longer and drive in certain areas by using the same visual simulations as a video game mechanic. Uber is basically mastering their workers mental circuitry to get employees to work when they want and I find this interesting and it makes me wonder how many other jobs uses this technique.

  • https://fivethirtyeight.com/features/unc-played-ugly-enough-to-win/

    So this article was interesting to me because I watched the whole championship game between Gonzaga and UNC, and boy was it ugly. Between the fouls and the overall poor fg% as the article points out, it made the game slow, choppy and difficult to watch. Like the author noted, it came down to which team played less worse, and in this case it turned out to be UNC. Congrats to them and my friend who won $240 because they played ugly enough to win.

  • http://www.post-gazette.com/sports/Pitt/2017/03/06/Sloan-Sports-Analytics-Conference-Boston-Data-driven-stats-geeks-make-their-mark-on-sports-Mark-Cuban-Nate-Silver/stories/201703060073?pgpageversion=pgevoke
    This article was very interesting to me, because I am a very big sports person as well as being very interested in the technology field. It is crazy to think how using complex systems may be used translate to perfect team chemistry, which will then translate to team success. This makes me really wonder how sports betting/gambling will be like in the future.

  • http://www.fangraphs.com/blogs/about-all-these-velocity-spikes/#more-249927
    The article discussed the increase in velocity for Major League pitchers already in the 2017 season. I thought it was interesting that despite the apparent increase in velocity, most pitchers still throw around the same velocity as last year, but the tracking systems changed. This year there was a change in where the velocity gets measured, which results in different data and large misconceptions for scouts or broadcasters.

  • https://www.zillow.com/research/housing-affordability-by-race-14670/
    This article highlights how a strong rental market, pushing monthly rents up, as disproportionately had a negative effect on low-income neighborhoods, and particularly on black renters. Rent increases, coupled with stagnation in income growth, have led to a situation in which average black renters in low-income neighborhoods now pay nearly 44% of their monthly income on rent, making it much more difficult to save up for down payments needed to purchase a home. Homeowners nationwide typically spend less than 30% of income on mortgage payments. Combined, this leads to a situation in which black renters are forced to rent for longer periods, thus committing a larger portion of their income to housing costs, and creating a cycle of being stuck without building wealth through equity in homeownership.

  • http://www.baseball-reference.com/teams/PHI/2016.shtml
    I picked an article on the Philadelphia Phillies from the 2016 season because I love the Phillies. It shows each player’s stats and what they accomplished that season. It also shows the team totals from the year and what the team as a whole accomplished. One of the stats that is shown is the players WAR. WAR stands for wins above replacement. The player with the best WAR was Odubel Herrera, who had a WAR of 4.3. That is above average for a major league player. Overall, I choose this article because it had all the stats from the Phillies 2016 season and I love the Phillies.

  • http://variety.com/2017/biz/news/donald-trump-net-neutrality-fight-privacy-stephen-colbert-1202020419/
    I picked this because I heard about congress passing a new legislation allowing internet providers to sell its users’ browsing data. When I first heard this I did not think much of it until I started thinking about it more. I was surprised that it got that far, especially the fact that I don’t think anyone would want this. I also felt as if this did not get enough news coverage, especially since it affects all people around the country.

  • http://www.pewsocialtrends.org/2017/03/23/americans-widely-support-paid-family-and-medical-leave-but-differ-over-specific-policies/
    I found this article is really interesting. This article is about the paid family and medical leave are well supported by Americans. The statistic here is the exact percentage of people, and in different aspects. It also shows that people who support paid leave expect the pay come from employers.

  • http://www.theverge.com/2017/4/4/15159148/norway-data-vault-svalberd-mine-storage

    This article examines the new ice planet file fabricated Toward those Norweigan organization Piql. The file serves Concerning illustration a remote spot to stay with vital information sheltered from common disasters Also worldwide clashes. A few national legislatures need saved their authentic documents Also other information in the vault already, and this information could make safeguarded for dependent upon 1000 quite some time with the film innovation organization that Piql need produced. Customers could send their information digitally or physically, What’s more appeal it during anytime, settling on those ice globe file those most secure spot to store information to a developed time about the long period of time.

  • https://www.theguardian.com/technology/2017/apr/04/uber-google-waymo-self-driving-cars
    This article is about the driving statistics published by California, it shows that Google is 5,000 times better than Uber at autonomous driving. The way to measure the autonomous driving solution is how often the driver has to take over to correct shortcomings in the autonomous driving software. I think the autonomous driving is going to strike the driving market, so it’s much more better to know which one have the greater probability to win the future competition with a better performance.

  • http://www.mckinsey.com/business-functions/marketing-and-sales/our-insights/the-heartbeat-of-modern-marketing?cid=soc-web

    McKinsey&Company discuss how marketers use data activation and personalization strategies to reach consumers in the moment – no matter where they are or what device they’re on. Customer Data Platforms give marketers the ability to scale this messaging in real-time once they “feed” the CDP with IF/THEN rules and data regression models. In turn, the CDP is able to deliver targeted communications once triggered by consumer data signals. With the influx of messaging that users receive on a daily basis, hyper-personalized marketing really breaks through the clutter.

  • http://www.techrepublic.com/article/5-steps-to-turn-your-companys-data-into-profit/
    The article is talking about how to use five steps to help businesses use their data to get the biggest business impact. First, discovery: focusing on the nature of the problems or opportunities the organization is facing. Second, decision analysis: begins to structure the analytical problem a company is addressing. Third, monetization strategy: determine if its solution has value, and the impact on business performance. Next, agile analytics: using guided analytics and decision theory to create an end solution. Finally, enablement: making sure the data is valid, the calculations are correct, and the end users are engaged in the testing process. I found the article is useful, since many company are still struggling to turn the information into business outcomes. This is what we have to learn about.

  • https://fivethirtyeight.com/features/we-rated-every-rotation-in-mlb-how-does-your-teams-stack-up/?addata=espn:clubhouse

    Being a pretty big Red Sox fan, I found this article to be interesting. In this article, fivethirtyeight ranks every MLB team’s pitching rotation. They score each team’s rotations based on performance, innings pitched in each game, dominance and number of runs allowed.

  • https://www.theguardian.com/lifeandstyle/datablog/2017/feb/09/national-pizza-day-how-many-slices-do-americans-eat
    The article I chose talked about American’s consumption of pizza. It shows that pizza is one of the only types of food that American would consume on any given day no matter what gender or ethnicity group they are from. It is also found that more than half of the consumption is seeing pizza as a snack, the second up option is lunch, and people rarely have pizza as dinner or breakfast. They also show the comparison between the data of pizza consumption with drinks. Although it is thought that people would consume more soda than juice, it also depends on the consumer’s background as well. Although I wish there would be more data to support their claims, I find the topic interesting because it is relevant to my daily life.

  • http://www.zdnet.com/article/commonwealth-bank-targets-smes-with-new-big-data-analytics-platform/

    Since I am interested in banking, I thought this article about a bank creating a new data analytics tool for small to medium sized businesses to use was a great article. The goal of the new tool is to empower the SMEs (small-to-medium enterprises) to use these tools to their advantage. Another goal is to make data analysis tools easier to use and to not require too much training. They hope to give these smaller companies access to big data and the power to know how to use it.

  • I find this https://www.clevelandfed.org/newsroom-and-events/publications/economic-trends/2015-economic-trends/et-20150331-racial-and-ethnic-differences-in-college-major-choice.aspx interesting because nowadays a lot of students have trouble with choosing the major for their college especially the immigrants who live in other countries. Just like me that, I need to consider more on job marketing other wise it will be harder for me to get a better job after graduate. For this link or article, it has worked well with their research on the major between Asian, black, white, or Hispanic in order to consider and choose the right major and make sure getting a better career future.

  • https://fivethirtyeight.com/features/james-harden-gets-fouled-on-3s-more-than-any-nba-team/
    I found that James Harden gets more fouls on 3s more than any other team interesting. James Harden has drawn 108 fouls on 3 point attempts while the highest team has drawn 73 fouls. This just shows that James Harden is on another level when drawing fouls.

  • http://www.omaha.com/money/we-want-to-move-fast-facebook-s-new-data-center/article_0ac9beb4-1943-11e7-8206-ef22f010baa4.html
    Mark Zuckerberg said yesterday: we’re building our ninth data center in Papillion, Nebraska. That means facebook needs extra data storage. Facebook bought Instagram in 2012. Facebook now has a stable growth of users. I was thinking how facebook picks these place for data center. “Facebook currently has data centers in Prineville, Oregon; Forest City, North Carolina; Lulea, Sweden; and Altoona, Iowa. Construction on additional data centers is underway in Fort Worth, Texas; Clonee, Ireland; Los Lunas, New Mexico; and Odense, Denmark.”(omaha.com) So I guess doesn’t matter for data storage.

  • http://flowingdata.com/2014/05/29/bars-versus-grocery-stores-around-the-world/

    This article has data visualizations that show which places in the US have more bars than grocery stores. I found it surprising that there are about 13% more grocery stores than bars, I expected there to be a lot more grocery stores than that. Some places, such as the entire state of Wisconsin, have an average of 2.7 times more bars than grocery stores. It seems that the more rural the area, the higher average of bars there are. This is most likely due to the fact that in a less populated area there is not a need for multiple grocery stores, but there will still be many bars.

  • Yesterday throughout social media and news sources I learned that it was Equal Pay Day, very interesting and a good social talk. Interesting enough I found an article named Equal Pay Day: a wage gap fact check, and the author Mona Chalabi investigates Equal Pay Day. She says, “That date is symbolic – it shows roughly how many days of 2017 women need to work to earn as much as men did in 2016. Tuesdays are symbolic too, they represent “how far into the next work week women must work to earn what men earned the previous week”. She also states that the wage gap is much larger than the 80 cents to the dollar myth and proves it with data.

    https://www.theguardian.com/us-news/datablog/2017/apr/04/equal-pay-day-us-wage-gap-gender-race-ethnicity

  • http://www.businessinsider.com/how-much-money-doctors-make-2017-4
    This article shows how much different types of doctors make a different amount of money. And also, if you didn’t know, race does play a role I the salary. Different races earn different amount of money. Such as in the graph it shows that the “white” doctors make the most out of all the races. This is related to me because, I actually might be switching my major because I want to make a lot of money after I graduate. And fro this article, I know how much doctors makes, and i know which type of doctor makes the most.

  • https://fivethirtyeight.com/features/americans-shift-to-the-suburbs-sped-up-last-year/
    As I get closer to graduation I certainly think about where it will be best to live after school. This article is very insightful and accurate about the location tendencies of individuals at various life stages, especially recent graduates, and in comparison, those who already have a career and possibly a famil. The data visualizations here show very large differences for suburban and urban living relative to scale.

  • http://www.ncaa.com/news/basketball-men/bracket-beat/2017-01-18/march-madness-brackets-how-often-we-pick-ncaa-tournament
    With the NCAA Tournament just ending on Monday I decided to try to find something that related to the tournament. In this case with so may people making brackets every year, I found an article that shows the percentage of people that pick each different seed, and the percentage of how often they get those picks right. I thought that it was very interesting to see which upsets that people tend to pick the most and least, and which upsets actually happen the most. It even talked about the average on how many seeds that are 10-15 on average make it past the first round every year.

  • https://www.suasnews.com/2017/03/comparable-maps-anytime-thanks-pix4d-sequoia-sunshine-sensor/
    This article is a report on the accuracy from 3D imaging data gained from drones. The new data shows that smarter drones and software make it able to get the same data about agriculture fields in any weather condition. It displays the levels of differences in data gained from the different software and also detailed how the maps created are now the same in various weather conditions.

  • https://www.nytimes.com/interactive/2016/02/14/us/supreme-court-justice-ideology-scalia.html?_r=0

    A current news story right now is President Trump’s and Republican senators’ struggle to confirm Federal Judge Neil Gorsuch to the Supreme Court. I found an excellent line graph showing all the political ideologies of every justice in the highest court of the land since 1940. If a justice’s line is vertically above 0, it means they lean towards the right. If it’s below, they lean left.

  • https://blogs.spectator.co.uk/2017/01/oxfam-wont-tell-capitalism-poverty/
    Growing up I always had a niche for entrepreneurship and free enterprise, the overall idea of independent work sounded amazing. This realization made me want to dive deeper to better understand it and in turn I discovered something. Free enterprise has been saving billions of lives from poverty. Country’s all over the world have given the opportunity for people to change their everyday reality. In this article I found a better explanation on the impact free enterprise has on the world’s poor and how without it billions of people would have lost their lives. Today Free enterprise has brought the poverty levels down to 10 percent and even though there is a lot of work that needs to be done this achievement is worth celebration. Today people are finding new discovers and changes through time faster than ever all because of data.

  • http://www.pewresearch.org/data-trend/society-and-demographics/parental-time-use/
    The article I chose displays average Parental Time Use. There are two different charts, one for mothers and one for fathers. The charts divide time into three sections; Childcare, Housework, and Paid Work. I found this particularly interesting because as I get older I wonder more and more what my future will be. If I will be a professional most of my life or a stay at home mom. I found it interesting how the amount of mothers with paid work has tripled in my lifetime.

  • http://www.pewsocialtrends.org/2017/03/23/americans-widely-support-paid-family-and-medical-leave-but-differ-over-specific-policies/

    This article is extremely interesting to me because I am currently in the middle of trying to change the PA Family Medical Leave Act with my mom. We have been trying to include siblings and parents in to the Family Medical Leave agenda for almost 8 years now. We have struggled with the bill passing because most politicians only care about themselves and don’t want actual positive change. So, the more information I can get on citizen’s support of medical leave, the better of my cause will be.

  • http://uproonline.com/index.php/UJCT/article/view/20
    The article i post because it introduces the ensembles of distributed, heterogeneous resources. It has 4 main parts, 2 of them specifically introduce the data management and data integration in grid computing environment. This paper is of interest to distributing computing researchers because Grid computing provides new challenges that need to be addressed.

  • http://www.stanforddaily.com/2017/04/05/big-data-and-the-creation-of-a-self-fulfilling-prophecy/
    The article is about the self-fulfilling prophecy of big data. I liked the example of the police taking an eye on the neighborhoods that come to have higher crime rates. The problem is that data on crime is often biased because arrests are more likely to occur in neighborhoods that are “monitored more often”. This article says that the algorithms used for data analysis are somewhat oppressive, and might isolate groups that are already at society’s margins. I thought this was a negative side that we should really think about, considering how much data analysis means to our societies more and more.

  • https://www.forbes.com/sites/adrianbridgwater/2017/04/04/teradata-the-7-pillars-of-big-data-culture/#30c7245ca93e

    This article is titled: “Big Data Culture,” and it discusses the world of big data analytics along with data science and how it is in their opinion “over-hyped” but also intriguing, equally. They summarized, in their term, the simplified elements of what gives “big data” potential. Articles that summarize and give minimalistic answers are easy eye-catching data visualizations, the title was also something I had never come across so I immediately clicked it.

  • http://flowingdata.com/2017/04/04/visual-simulations-to-show-uber-game-strategies/

    Very interesting to see that Uber uses very creative and smart ways to incentive drivers to work for a longer time and in certain areas.

  • http://www.predpol.com/hot-spot-policing/
    This informational article derived from a criminal justice symposium coordinated by the NIJ (National Institute of Justice) reveals a new form of crime mapping technology being used by many law enforcement agencies around the country. “PredPol” is a computer based program that collects aggregate crime data from previously identified “hotspots” (regions where specific types of crime frequently occur) to predict future criminal activity that will likely spawn within adjacent locations later in time. A series of confidence intervals (% of likelihood where an incident is bound to occur) are examined to anticipate when different types of crimes will be dispersed among certain areas by reviewing statistical trends. Data analysis tools like these help facilitate a more proactive style of policing (responding to incidents BEFORE they happen), rather than relying on individually reported call-outs to dictate response priority. The nature of police work in today’s day and age is undoubtedly stressful and dangerous, but with technological resources like PredPol and its counterpart COMPSTAT (Computerized Statistics) at an officer’s disposal, this allows for police to respond with greater preparedness.

  • http://www.nature.com/news/smart-manufacturing-must-embrace-big-data-1.21760

    This article talks about the manufacturing industry and how that it needs to embrace big data in order to be successful in the future. When this happens, manufacturers will be able to adapt to changes in customers, products, and various other variables much more quickly and effectively than before. They can also use the data to improve on energy and healthcare for their workers in the factories in such. It needs to happen sooner than later as well, because society is progressing at an extremely quick pace.

  • https://www.washingtonpost.com/news/fancy-stats/wp/2017/03/13/2017-ncaa-tournament-the-perfect-bracket-to-win-your-march-madness-pool/?utm_term=.42b9989b8616
    This is an article which gives insight on to who people should pick for their brackets based on a couple different statistics and projections. I thought ut was interesting to look at their reasoning, and also to see how they did now that the tournament is over.

  • https://www.fastcompany.com/3014911/top-10-iconic-data-graphics
    In this article there are some very good data mapping and infographics. Like windmap, gapminder, The Ebb and Flow Streamgraph, Paths to the White House, Death and Taxes, Gay Rights, State By State, Bikini Chart, A Peek Into Netflix Queues, Why Is Her Paycheck Smaller?, How Common is Your Birthday?. These were very interesting for me.

  • http://www.economist.com/blogs/graphicdetail/2017/04/daily-chart-0

    I think this article is interesting because dunk driving is a large problem. Especially among college students, it sheds light on all the positive aspects of ride hailing apps. Its helping to create a more responsible a contentious generation. It also has helped to create a zero tolerance for drunk driving. Their is now absolutely not exceptions.

  • http://www.pewinternet.org/2017/01/26/americans-and-cybersecurity/

    Internet is our daily, almost everyone uses it to do each kind of things. Crime in the reality and so does the internet. Hackers may get our personal information if we don’t learn how do protect them. A majority of Americans (64%) have personally experienced a major data breach, and relatively large shares of the public lack trust in key institutions – especially the federal government and social media sites – to protect their personal information.

  • http://foodfitphilly.org/eat-healthy-on-a-budget/ I think this article is interesting because it gives you information on how to spend the most of your money. It supports local small-business corner store owners. the article shows what corner stores you can visit with what budget to get the healthiest food possible. With obesity rates so high, information like this can only help the local community.

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Office Hours

Joe Spagnoletti (instructor)

Office: Speakman 207H

Hours: (1:20-1:50, 3:00) M, W, F by appointment.

Email: joespag@temple.edu

TA: Prince Patel

Email: Prince@temple.edu