Laurel Miller

https://www.theguardian.com/business/live/2019/sep/06/germany-industrial-eurozone-recession-brexit-sterling-non-farm-payrolls-us-dollar-jobs-report-business-live

Data give “a convincing signal that Germany is in recession”

As a journalism and economics major taking this class, an article from a newspaper outlet sharing trends on a country’s economy amid a trade war to predict a recession is of high interest to me. I admire the journalists getting opinions from economists at different outlets and noting the day-to-day change in data. I also find the role of journalism here interesting as it is 1) highlighting public data, 2) explaining the data and how what the data is suggesting could impact citizens, 3) holding economists accountable in reporting changing trends, and 4) being an independent outlet to track, compile, analyze, and share data, interesting.

https://www.wsj.com/articles/global-stocks-waver-ahead-of-jobs-report-11567757633

As an Accounting & Finance dual major, the stock market and understanding economic outlooks is my favorite part about the business field. The current stock markets have been very shaky in terms of what the next few years will look like. Last week, news hit about the Fed cutting short term interest rates and the labor department said that the U.S. added 130,000 jobs but was predicted to add 150,000; this kept the unemployment rate consistent at 3.7%. The imminent economic health of the United States is neither recessionary or growing rapidly. In response to this news, the S&P 500, Dow Jones Industrial Average, and Nasdaq all ended the week up at least 1.5%.

https://www.reuters.com/article/us-tesla-markel-insurance/teslas-use-of-individual-driver-data-for-insurance-state-by-state-proposition-idUSKCN1VQ0FY

This article discusses a use of data. Tesla gathers driver data through cameras in their cars, which they plan to use to help price individual driver’s auto insurance with the driver’s authorization and where state laws allow. This is interesting for me as an actuarial science major, as it can have an effect on the way that auto insurance is priced in some instances. Along with this, the article discusses the belief that self driving technology should cause decreases in auto insurance prices and increases in safety, but there isn’t enough data to be able to really draw this conclusion yet.

https://www.theguardian.com/us-news/datablog/2019/jul/14/diabetes-insulin-mona-chalabi-data-blog

As an Actuarial Science major, the insurance industry is the single most important field in the business world to me. This article described how the pharmaceutical and insurance industries are raising prices of insulin, a drug essential to those with diabetes. The main argument is that non-white Americans are getting hit the hardest with the increasing prices and I find the provided data very supportive. The article provides data such as what proportion of Americans are insured and which races have a higher proportion of diabetic members. I think that the author did a fantastic job incorporating emotion into the article by including data about how people ration insulin and the death rates associated with it.

https://www.healthcareitnews.com/news/how-solve-goldilocks-dilemma-health-data-sharing

This article discusses the balance between making healthcare data available and protecting patient security. I found it interesting as I worked in healthcare IT consulting over the summer and will continue after graduation. Changes to data security laws like this are very important factors in how we can advise payers and providers, especially as the article says there are calls for changes to HIPAA. Information security protocols are being put more and more in place and we have to figure out what is ethical while also using the data we have for good such as improving patient experience and lowering prices where possible.

We Found The One Edge Your NFL Bets Might Have Over Vegas

This article talks about how betting on the “unders” on NFL win totals may lead to a push or even win for the bettor. This analysis looked at all NFL win/loss data form 2003 to 2018 and examined the relationship between the Vegas expected wins vs. what actually happened in the season. As a Statistics major and avid sports fan, I find this very interesting as it almost appears as though there is a way to beat the house in betting and is performed through analysis of the data, which I have done a lot of in my statistics classes. They also note that this trend does not exist for this current season, which means that Vegas may have used this same data to right their issue.

https://www.washingtonpost.com/graphics/2019/investigations/pharmacies-pain-pill-map/

This investigative piece on “How many pain pills went to your pharmacy?” is a fascinating article analyzing and visualizing data on the opioid crisis in the United States. As a global studies major on the global security track, the opioid crisis and drugs in general are of interest to me academically and personally. Their data visualization tool, which allows readers to search for their pharmacy, is incredibly interesting and an effective use of data. I also think the map of the United States showing areas with high volumes of opioids is extremely well done. The article also includes other accessible data visualizations with detailed analysis.

Where Salaries Go Furthest in 2019: The Small-City Advantage

I thought that big cities can earn more money than small cities. But, in this article, actually, when considering the cost of living, the salaries are higher in small metropolitans. The data shows that San Jose, San Francisco, and other California metros have the highest salaries before adjusting the cost of living. But after adjusting the cost of living, these cities are not the highest-salary metros. However, the small-city advantage does not hold for finance and tech fields. The article explains why there is a difference between tech and other jobs. It is because “the fact that unadjusted salaries are higher in bigger cities means that employers pay a premium to hire there — 7% for all jobs on average and 27% for tech jobs”.

https://www.billboard.com/articles/business/chart-beat/8528285/taylor-swift-lover-us-biggest-sales-week-first-dayv

This article compares data of the sales of best selling albums released in 2019. This is relevant to my major as it shoes how powerful a properly executed advertising campaign can be, when most people say people will soon stop buying cd’s, some artists still manage to get record breaking sales.

Conspiracy Theories Can’t Be Stopped

This article discusses conspiracy theories. Conspiracy theories tend to “punch up”. People of lower social or economic status are more likely to engage with conspiracies. Additionally, conspiracies are often about people in power.

https://www.edweek.org/ew/articles/2018/03/21/schools-struggle-to-use-data-to-get.html

This article is about how data can be useful to teachers in helping their students. As an education major, I would like to acquire all of the tools necessary to be the best teacher possible. This article describes how data can allow teachers to “identify student needs” and help them. I think that data can be very useful and, in a way, teachers have been using it for years. Grades are a form of data in that they quantify students’ abilities. Seeing the patterns of grades in a student can allow a teacher to gain insight into how that student learns.

https://www.cnbc.com/2019/09/10/us-job-openings-decline-for-second-straight-month.html

This article offers data about job growth in the United States from July to August. As a freshman with an undecided business major, I have very little experience or knowledge about the economy. However, my micro and macroeconomics classes briefly discussed this topic, and I find it fascinating that economists can predict what may happen to the economy due to slight differences in job openings rate (4.6% to 4.5%). I hope that with further studying, I can broaden my own knowledge about what these subtle differences could mean for the future.

https://www.forbes.com/sites/stephanzoder/2019/09/10/nevada-takes-a-different-approach-to-data-privacy/#2d30fac037be

Nevada Takes A Different Approach To Data Privacy

This article discussed the new data privacy law that has just been passed in Nevada which is set to take effect in October, 2019. This Nevada law has some significant different with similar laws enacted in California (CCPA) and Europe (GDPR) in that it constitutes a “opt-out” instead of “opt-in” approach to data privacy. The article also discusses some challenges and potential risks in complying with this law as well as similar laws. As a risk management and insurance major, I find this article interesting because it shows that data privacy laws can be different in different areas, which makes compliance more difficulty and costly. It also exposes firms, especially multi-state and multi-national firms, to increased liability exposures. The dynamic nature of data privacy laws will soon to be an important risk management issue.

https://www.theguardian.com/news/datablog/2019/aug/24/family-separation-immigration-kids-mental-health-trump
This article has to do with children that are separated from their parents at a young age and how children that experience this are more likely to experience anxiety and depression later on in life. The length of the separation also matters. Children who are separated from their parents for two or less years are less likely to experience high levels of anxiety and depression than those who are separated from their parents for two to four years. This is relevant to my field of study because I am a Political Science and Spanish major, This article addresses specifically the crisis at the U.S. border with Mexico and the detaining and separation of asylum seekers (especially parents and their children) that is occurring. The article discusses a study about adolescents who had migrated and undergone family separation at a young age and how it affected them.

Is It Really A Three-Candidate Race?

As an Actuarial Science major, the presidential election can have a huge impact on my future career. Possible healthcare legislation by presidential candidates can affect my work after college. This article was interesting to me because there are currently over 10 candidates in the Democratic Primary race, yet this article claims that only 3 candidates have a chance at winning the nomination. The article also explains that even the current favorite Joe Biden can still implode and not win the nomination This would be very surprising since the data says he is polling at almost double of what the closest competitor. The data points towards Biden winning easily, but as we saw in the past presidential election, polling may mean nothing.

One conventional wisdom I have heard is that states in the United States with the death penalty have lower crime rates. The belief is that the death penalty will deter people from committing crimes, as doing so could result in death. To test this conventional wisdom, I could find the states who have the death penalty as well as those who do not have the death penalty and find each of their crime rates. I would then compare the data to see if the states with the death penalty have lower crime rates.

One conventional wisdom that I hear often especially now is that people with higher GPA’s end up with a better job / with more opportunities than people with lower GPA’s. In order to actually put this to the test, I can look at the median salary for college graduates who graduated Cum Laude and the median salary for those who graduated below the top 25%. We can look at the progression of graduates throughout their careers to see the long term impact. This will show us if having a higher GPA actually results with a higher salary both short term and long term.

One piece of conventional wisdom is that cities are less safe than more suburban and rural areas. In order to test this, I would collect data on populations of various cities, suburbs, and rural areas as well as their crime rates. By correlating these data points, I would be able to tell if more densely populated areas are really less safe than those with lower population density.

An example of conventional wisdom is that movies without famous actors or actresses can’t succeed in theaters. To test this, I would collect opening weekend total box office sales for movies in a given year with and without oscar-winning actors and actresses. I would compare the total sales for movies with oscar winners actors and without oscar-winning actors and see if one category had more significant sales, and if so, if there is a considerable enough difference to make the claim that one category can or cannot “succeed.”

A piece of conventional wisdom that I’ve heard is that students who use planners and calendars are more successful in school. I could test this by surveying students with the same class and professor and determining which ones use planners. By separating students into two groups (one with planners and one without) and calculating their median grades, I can figure out if planners have any factor in higher grades.

An example of conventional wisdom that I have heard is that the more money spent on a campaign, the more likely a candidate is to win. The data needed to prove this would be the amount of money that candidates spend and the results of those campaigns.

A common example of conventional wisdom is the poor reputation of young drivers. Insurance companies consider younger drivers higher risk for many reasons. In order to test it, one could collect data such as annual deaths and injuries in vehicle crashes, annual medical costs from vehicle crashes, and annual auto repair costs from vehicles. Each of these data would be filtered by age ranges in order to compare totals for different age groups.

One example of conventional wisdom I heard is that students who have internship experience tending to find a job easier than those who do not. To test this, I will do a survey to ask whether they have an internship or not before they are finding the job and the difficulty of getting a job after they graduate. I will compare those data to find out if the students with internship tend to find a job easier.

One example of conventional wisdom is that people with tattoos are less likely to get certain jobs. The best way to see if this is true would be to send out a survey asking if the survey takers had tattoos, how many they have if applicable, and what their job is. The data from this survey could then be analyzed to see if having tattoos prevents individuals from having certain types of jobs.

One example of conventional wisdom is that you need an advanced degree in order to be financially successful in life. In order to test this, In order to test this, I would collect income data on high-school graduates, college graduates, graduate school graduates, and trade school graduates. While I suspect that college and graduate students will have high income, I also believe that trade school students are able to be successful through their specialization. Through this test, I would be able to reach a conclusion on what level of education is needed in order to be financially successful.

An example of conventional wisdom that I hear around campus is that business students have better career prospects than students in CLA or any of the other non-business schools at Temple. To test this, I think the two main data points to collect would be salary and job satisfaction. I would collect data regarding these two pieces of data for a sample of Temple graduates from the different schools at different stages of their careers (one year out of school, five years out of school, etc.) to determine whether business students actually have the best careers in terms of salary and fulfillment.

One example of conventional wisdom is that store/generic brands are worse quality than name brands because they are cheaper. This is common for things like household items and self care products like face/body wash. Data that could be collected to test this would be the ingredients of both products and opinions of users in focus groups or experiments in which people use both products in a blind testing. If all are equal or the store brand is rated better then the name brand then this could be disproven.

A example of conventional wisdom that I have heard many times is that people with tattoos are less likely to get hired and will have less successful careers. While that concept has been dropping in popularity, we still hear about it every so often when dealing with the business world. To test whether or not tattoos have an effect on job placement, I could collect data on people who have tattoos and what jobs they have had.

A piece of conventional wisdom I often hear is that people with college degrees (for the purpose of this, a Bachelor’s) make more money than those without college degrees. To test this, I would collect data on two populations at the same age in the United States: people who have successfully completed a Bachelor’s degree, and people who have not. I would then compare this data by finding the mean and median salaries for each of the two populations. By doing this, we can analyze if people who have completed a college degree have generally made more money in their post-grad careers than those who did not, or if there is no significant difference.

A piece of conventional wisdom I’ve heard is that books will soon be extinct in favor of e-books. I could collect sales data from multiple bookstores over a few years to see if the the sales are actually declining, and get data from e-book sales as well to compare how much those are actually rising. By analyzing them both together I could see if there’s a pattern that would either support on contradict that statement.

One piece of conventional wisdom that I have heard before from older generations that if someone has bad eye contact they are not trustworthy or a liar, operating off of the assumption that this person is too afraid to look at you in the eyes because they are lying. I would test this assumption by having a mixed group of convicted thieves or criminals and people with clean records. I would then talk to each one for a minute, evaluate their eye contact and guess whether they were trustworthy or not based off their eye contact. I would then reveal the identities of each person and see how many I had correctly identified as trustworthy or not trustworthy off their eye contact.